22 PAPR Peak-to-Average Power Ratio. 49 PD Photodetector. 1 PDF Probability Density Function. 19 PIR Packet Inter-Reception. 48 PPM Pulse Position Modulation. 1 ProSe Proximity

Keywords: 3GPP Third Generation Partnership Project, 3 5G-NR 5G-New Radio, 11 Aperture Averaging, 15 ACLR Adjacent Channel Leakage Ratio, 49 ACO-OFDM Asymmetrically Clipped Optical OFDM, 1 ADC Analog to Digital Converter, 49 AMS Adaptive Modulation Scheme, 4 AP Access Point, 4 ARIB Association of Radio Industries and Businesses, 11 ARQ Automatic repeat request, 60 ASP Analog signal Processing, 49 ASTM American Society for Testing and Materials International, 11 Semiconductors, 50 CoMP Coordinated Multi-Point, 15 CSI Channel State Information, 25 USRP Universal Software Radio Peripheral, 40 UTROV Un Tethered Remotely Operated Vehicle, 10 UV Ultra

During the last decade, the exponential growth of mobile devices and wireless applications induced an enormous demand for radio frequency (RF) technologies which in return requires more and more resources from both the connecting devices and the supporting network infrastructures. Spectrum crunch is a term referred to the network traffic overload and the infrastructure ability to meet the user demands because of limited resources. In recent years, many strategies have been adopted to make the most of these precious resources, such as reusing the available frequency band, and/or discovering new bands such as millimeter and Tera-hertz waves. Meanwhile, the Visible Light Communications (VLC) demonstrate huge capacity to supplement the conventional RF technology, including unlicensed and free massive spectrum band, which provides the communication service along with illumination at a convenient price. Despite its vast potential applications and available infrastructures, VLC is still in its infancy and has a long way to pave in order to join the heterogeneous architectures. At this time, the majority of scientific research has been conducted around the physical and data link layers with emphasis on the point to point communication, while the development on the upper layers has been partially neglected. Certainly, the stable connection at the "decent rate" is the key objective of the medium access control layer which is acquired through different techniques such as handover, multiple access, association, disassociation and adaptive modulation and coding schemes. In this doctoral dissertation entitled as "Communication protocols based on alternative paradigm for wireless mobile devices", VLC has been initially used to address vehicular communication challenges as a main application at MAC layer, by integrating VLC and cellular vehicular to everything (C-V2X). The main contributions of this PhD thesis are as follows: 1-study and derive a communication model for outdoor VLC applications using open source simulating tools, 2-design and apply link adaptive protocols to associate, transmit and modify the communication session in VLC mobile scenarios, 3-develop, implement and test the interference based handover mechanism in small scale testbed, 4-comprehensive comparison between LTE-V2X and V2LC performances in ad-hoc regime, 5-design and perform the RF-V2LC protocol for cooperative VLC and LTE in vehicular network. These contributions have been performed through deep understanding of the up to date literature, interpret, compare and analyze the recent associated researches and developments in order to provide the reliable outcomes in VLC communication protocols for mobile devices.

The ever-increasing number of mobile devices and wireless applications induces an extensive demand for Radio Frequency (RF) spectrum.

According to [START_REF]Cisco Annual Internet Report[END_REF] The total number of global mobile subscribers will grow from 5.1 billion (66 percent of the world's population) in 2018 to 5.7 billion (71 percent of the world's population) by 2023. During the same period, connected home applications will have nearly half or 48 percent of Machine-to-Machine (M2M) share by 2023 and connected car applications will grow the fastest at a Compound Annual Growth Rate (CAGR) of 30 percent. Higher cost and limited free RF spectrum to host further mobile data traffic call for an alternative communication medium to offload traffic from the RF spectrum and provide more capacity.

Visible Light Communication

In recent years many technologies have been presented to solve the "spectrum crunch" problem, meanwhile Visible Light Communication (VLC) demonstrate a great capacity to complement the RF systems including the huge unregulated bandwidth, immunity to interference with RF technologies, free-of-charge operations, and several other benefits. Visible light is a portion of the electromagnetic spectrum that is visible to human eyes and falls between 430 and 770 nanometers of wavelength. VLC is a subset of optical wireless communication (OWC) that employs this part of the electromagnetic spectrum for wireless transmission, in the other words, VLC uses visible light as a carrier for data transmission and can be applied to many communication scenarios. For example, VLC can be used in electromagnetic waves restricted zones such as hospitals and airplanes, or it can be applicable in underwater communications where the seawater penetration is high [START_REF] Chi | Visible Light Communication in 6G: Advances, Challenges, and Prospects[END_REF]. Affordable and widespread applications of the LED in the automotive industry grab the attention of VLC standardization efforts and R&D studies in this market. The communication service of LED is based on high-speed Intensity Modulation (IM) that is transparent to human eyes without any adverse effects on illumination level. The principal element responsible for Direct Detection (DD) in the receiver side of the VLC system is the Photodetector (PD). PD including phototransistors and photodiodes collect the light radiation and transform it proportionally to electrical voltage or current signals. Thus, VLC employs Intensity Modulation and Direct Detection (IM/DD) for data transmission where the instantaneous radiated optical power is determined by the signal amplitude which is non-negative and real-valued. These constraints limit the choices of effective modulation schemes used in VLC systems. Single carrier modulation techniques such as Pulse Position Modulation (PPM) and On-Off Keying (OOK) were initially considered for low-rate data transmission in VLC studies while recently the sophisticated Orthogonal Frequency Division Multiplexing (OFDM) such as Direct Current biased Optical OFDM (DCO-OFDM) and Asymmetrically Clipped Optical OFDM (ACO-OFDM) have been adopted. Alongside the drawbacks inherited from intensity modulation, the Line of Sight (LoS) restriction makes practical employment of VLC challenging. LoS is the most interesting scenario in various VLC systems where the optical lens concentrates the light on a narrow beam with minimal power consumption and a high power flux density on the photodiode. Moreover, LoS system does not suffer from multi-path distortions, and the noises from ambient light sources are substantially rejected with a narrow Field of View (FoV) at the receiver. However, the directionality may limit the communication range, and consequently, multiple VLC setups are needed to fully cover an area. In mobile communications, keeping the transmitter and the receiver in close alignment is the most challenging task, which has been dealt with by means of mobility management techniques. Future development of the VLC technology is subjected to increasing the robustness against noise and interference. The nature of the noise in VLC systems depends on the light flux hitting the PD. For instance, in outdoor applications, sunlight is the main source of noise while incandescent or fluorescent lamps create the major ambient noise indoors. Interference in VLC systems occurs when the signal from neighboring transmitters lands on the sensor. Although the interference and the noise can be from very different natures, however, they account for channel disturbances and degrade the performance of the VLC systems. In addition to the indicated Point-to-Point (P2P) challenges, VLC as a complementary technology needs to be integrated with the heterogeneous networks [3] [4]. Channel access, guaranteed time slot management, frame validation, association and disassociation, beacon management, and mobility management require further efforts on upper layers.

Vehicular Communications

In Intelligent Transportation system (ITS), Vehicular Communication (VC) include vehicles and other communication entities around it such as roadside infrastructures, networks, and the devices carried by individuals and pedestrians, setting up a reliable and scalable communication link between Vehicle to Vehicle (V2V), Vehicle to Infrastructure (V2I), and Vehicle to Pedestrian (V2P). Vehicle to Everything (V2X) enables the vehicle to communicate with its surroundings to disseminate and collect a variety of safety, infotainment, mobility, and environmental information in order to increase safety on the road and the driving experience. Safety applications supply drivers with information ranging from weather conditions, road construction, speed limits, and many other factors necessary to avoid accidents. Non-safety applications, on the other hand, include services related to the environment, maintenance, mobility infotainment, etc. The driver from its dashboard can access infotainment services such as multimedia, TV, messaging, navigation, calling, and many other applications available nowadays on smartphones. However, Quality of Service (QoS) and Quality of Experience (QoE) are essential issues in vehicular communication because of their high mobility and dynamic network topology. Car-Manufacturing companies such as Ford, Volvo, and BMW are adopting the available wireless technologies to provide safety and non-safety applications. DSRC and cellular networks are the most employed Radio Access Technologie (RAT) in V2X communications. The Dedicated Short Range Communication (DSRC) was primarily deployed to ensure traffic efficiency and road safety through 3 Mbps bandwidth at 5.9 GHz in Europe. After launching the early version of LTE/4G in 2008, the first standard for Cellular V2X (C-V2X) was introduced in the Third Generation Partnership Project (3GPP) Release 14 and completed in September 2016. It uses an upgraded Device to Device (D2D) interface called PC5 to enable V2V links in high-density and high-speed scenarios. However, the significant Doppler shift due to high velocity degrades the performance of V2X radio access technologies. Moreover, excessive resource collision from the random resource allocation mechanism increase the packet loss and the packet delay in high-density scenarios. Finally, the lack of orthogonal resources in covered areas, as well as synchronized resources (infrastructures) in remote scenarios calls for an alternative paradigm to enhance the V2X performance [5].

Vehicular VLC

Vehicular Visible Light Communication (V2LC) represents one of the most attractive paradigms of V2X. The aim of V2LC like other VC mediums is to exchange information between generic vehicles and their surroundings in order to improve the safety and driving experience on the roads. Different from RF-based solutions (DSRC, C-V2X) that have congested licensed-band, complex structure, and high deployment cost, vehicular VLC is a less complex, unlicensed, low cost, reliable, low energy, efficient, secured, and interference-free solution. Widespread employment of LEDs in car lumps, traffic lights as well as control cameras and sensors in ITS, lends additional motivation for researchers and industries to invest in vehicular applications using VLC. Platooning is a popular application in Vehicular communications where autonomous vehicles are accessing each other's information and are grouped within close proximity. VLC can assist the safety message dissemination in multiplatoon 1 when the performance of the dominant RAT degrades due 1: Multiplatoon is an enhanced version of platooning chain where the platoons follow one another to congestion [START_REF] Ucar | Visible light communication assisted safety message dissemination in multiplatoon[END_REF]. Directive features of LED (LoS propagation) provide highly accurate positioning of neighbors. Furthermore, Intel's scientists see excellent opportunities for VLC in automobile applications including adaptive cruise control, cooperative driving, collision avoidance, and even autonomous driving [5]. Vehicular applications of VLC technology remain potential in the presence of some critical issues such as an effective handover mechanism for efficient mobility management, Quality of Service (QoS) stability through VLC integration to the vehicular radio access technologies (C-V2X) as well as adaptive resource allocation and medium access process. As a matter of fact, to make VLC more operational in a real vehicular environment, an efficient design of Medium Access Control (MAC) protocol is required to ensure a seamless exchange of information in challenging V2X natures coming from high dynamicity, environmental disturbances, and co-channel interference.

Objectives and Contributions

Early studies on VLC technology have proven that it is highly applicable to vehicular communication. However, the current trend in VLC research is mainly restricted to the Physical aspects of LoS links such as noise mitigation and interference avoidance and new modulation techniques. The context of V2LC is highly dynamic rather than costly to implement. So the first challenge is to design and test an accurate model of an outdoor VLC channel. For this part, a channel model has been implemented which encounters two well-known signal attenuation: the sunlight shot noise and the climate fluctuation with atmosphere distortion index. This pragmatic channel model includes the Lambertian channel loss and statistical climate impairments that have been implemented on the opensource NS-3 simulating tool and tested for different outdoor illuminance ranges. 2 Under vibrant V2LC channel parameters including the front-2: Realistic simulation tools facilitate analyzing different channel factors and examination of new MAC algorithms. end orientation, transmitter-receiver path loss, and climate conditions, the link performance is extremely time-variant, and having a precise evaluation of the channel quality requires a continuous sensing state along with the constant discovery of pilot messages. The pilot message periodicity has a massive impact on the link evaluation and MAC protocol efficiency. This parameter is discussed in the Link Adaptive Protocol (LAP) to find a compromise between the protocol overhead and the link performance in terms of goodput and outage probability. LAP is the 3-step MAC protocol developed originally in this thesis to make a quick connection when the VLC link is available, it adjusts the data rate based on the quality of the link, and moves to other links when the quality of the current link degrades. Link quality in VLC is typically evaluated through Signal to Noise Ratio (SNR) and the corresponding Bit Error Rate (BER), ignoring any signal disturbances due to interference from other transmitters. The more accurate channel assessment is given by Signal to Interference and Noise Ratio (SINR) taking into account the normal distribution of interference and noise and the in-range variance of the disturbances. In contrast, the interference and noise distribution is depending on the dominant disturbance and are not always in the same range. The Interference based haNdover mechanism for VISIBle Light nEtworks (INVISIBLE) represents a new handover mechanism based on innovative link evaluation metrics called Interference to Noise Ratio (INR) and Interferer to Interference Ratio (IIR). In this handover mechanism, the dominant interferer has been selected as an Access Point (AP) candidate if its INR and IIR factors respect the thresholds. Eventually, among all the AP candidates the QoS requirement defines the handover host. This algorithm comes with an Adaptive Modulation Scheme (AMS) to further enhance the spectrum efficiency and prolong the connectivity. The performance of the invisible handover mechanism has been evaluated through extensive simulations based on the NS3 simulator tool and experimental validation in a small-scale version scenario in terms of handover rate, delivered traffic per handover, and handover delay ratio. The good match between the simulation and experiment results proves the faithful performance evaluation of the proposed handover and transmission mechanism.

As it has been mentioned earlier, one of the most interesting advantages of VLC in vehicular applications is the pre-existing infrastructure, which is apparently compatible with cellular V2X. To demonstrate the efficiency of the VLC performance in V2X communication, a comprehensive study on V2LC has been carried out and compared to C-V2X, regarding the energy consumption, Packet Reception Ratio (PRR), and end-to-end latency. Based on the achieved results, the vertical handover mechanism has been implemented to guarantee the predefined 3GPP baseline for Cooperative Awareness Messages (CAM). The harmonical Cellular Vehicular VLC (CV2LC) network assures the safety message delivery at the lowest energy cost and lowest delay.

Manuscript outline

This manuscript is arranged into five chapters: Chapter 1 introduces the general concepts of VLC, the advantages, the challenges as well as the potential applications including vehicular VLC. It is also including the motivations behind this thesis and the main contributions. In Chapter 2 the related works have been narrated starting from a brief history of OWC to the most recent novelties in V2LC. It provides background knowledge for the general viewers as well. Chapter 3 represents the first bunch of contributions of this work. It contains the realistic channel model realized on the open-source simulation tool, along with link adaptive protocol and its performance evaluation. The interference-based horizontal handover mechanism has been presented in Chapter 4. This chapter includes an interesting discussion on the handover delay ratio in simulation and the testbed too. In Chapter 5, a comprehensive comparison between two vehicular ad-hoc networks namely V2LC and C-V2X has been carried out. This chapter points out the major energy-consuming components of VLC and LTE transceivers based on a valid theoretical power model. Additionally, the Vehicular VLC shows a better performance in high-density scenarios in terms of latency and packet reception ratio. Based on these parameters, the CV2LC handover mechanism has been developed to guarantee the seamless dissemination of CAM messages at a relatively low price. Finally, Chapter 6 is the outcomes synthesis of this thesis, discussion regarding the contributions and the future potential steps. This thesis has been carried out in the "Institut national de The Growing number of mobile devices and their applications, enforces a huge amount of data exchange among mobile nodes and infrastructures, thereby, pushing the available RF technologies resources to their limit. VLC is a new paradigm that appeared to complement RF technologies in addressing the RF spectrum crunch. In this chapter first a brief summary of OWC is presented, then a more detailed VLC link and its characteristics are outlined. Later on, the interesting applications of VLC and their challenges will be discussed, and finally, the most innovative solutions to these challenges from recent academic literature are examined.

VLC

Optical communication is any kind of telecommunication that uses light as the transmission medium. Historically, optical wireless communication (OWC) originates in the form of beacon fires and smokes to convey a message in old cultures. In 1588, an army of 130 Spanish battleships known as the Spanish Armada set off from Flanders with the aim of invading England and overthrowing Queen Elizabeth I. When the fleet was spotted off the shore, a system of interlinking beacons was lit along the South Coast from Cornwall to London, to give warning of the arrival of the invading army. This rudimentary but effective system meant that English sea captain Sir Francis Drake and his men had time to prepare defenses and gather weapons. Drake's ships were able to stop the invasion and defeat the Spanish fleet before it could reach the English shore 1 .

1: https://www.atlasobscura.com/ places/armada-beacon, Published on July 25, 2018 While after, the heliograph was the standard wireless solar telegraph between British and Australian armies until the 1960s. The heliograph was a semaphore system that reflects the sunlight by pivoting a mirror in a given order (e.g., to generate the Morse code). In 1880, Alexander Graham Bell was able to modulate a voice message to a light signal and employs Free Space Optical (FSO) link to transmit it. Figure 2.2 shows the sketch of his Photophone including a vibrant mirror at the transmitter and crystalline selenium cells at the focal point of a parabolic receiver [START_REF] Bell | Selenium and the Photophone[END_REF]. The recent advancement in OWC technology gained a higher pace after and use different infrastructures. VLC uses light emitting diode (LED) as the transmitter, a photodetector (PD) as a receiver, and visible light (VL) as a communication medium. LiFi is the optical equivalent of Wireless Fidelity (WiFi). In LiFi, the PDs are used as a receiver, and the LEDs or defused Laser Diode (LD) infrastructures are dual-used for co-located lighting and wireless communications [START_REF] Koonen | Indoor Optical Wireless Systems: Technology, Trends, and Applications[END_REF]. It uses the VL for the uplink and the Infrared (IR) or VL for the downlink. The OCC uses an LED array as a transmitter and a camera or image sensor as a receiver. The communication medium of OCC is normally VL or IR, but Ultra Violate (UV) also can be used. FSO technology utilizes LD as a transmitter and PD as the receiver, while the communication medium is normally IR rather than UV and VL. The performance metrics of these technologies are represented in table 2.1 [9].

Nowadays, increasing the popularity of smartphones and their applications (nearly 300 billion mobile applications), the wireless data traffic exchanged among connected devices is growing exponentially. According to Cisco annual report [START_REF]Cisco Annual Internet Report[END_REF] nearly two-thirds of the global population will have Internet access by 2023-5.3 billion internet users equal to 66% of the global population-70% of them are through mobile connections.

Globally, mobile data traffic in 2021 approximated 48.3 Exabytes per month which is 23 times the volume of the entire Global Internet in 2005 [START_REF]Highlights of Cisco's Internet Traffic Report and Forecast[END_REF]. While the mobile data traffic demands continue to increase, the technical advancements and novel standards saturate the network spectral efficiency, and the concerns about the "RF spectrum crisis" becomes alarming [START_REF] Dimitrov | Principles of LED Light Communications: Towards Networked Li-Fi[END_REF]. Therefore, the acquisition competition on the limited RF spectrum increases the assignment price and induces security issues. Recent complementary wireless transmission techniques have been explored in order to relieve the spectrum occupation. They can be divided in two main categories: spectrum sharing, and spectrum discovery. Spectrum sharing is relying on central resource management unit to re-use the spectrum resources when they are not used by the owner licensed owner, or to use it non-adjacent geographical cells simultaneously such as cognitive radio [13]. On the other hand, spectrum discovery is trying to find empty rooms in higher frequency bands for example terahertz and millimeter wave [START_REF] Bauer | Terahertz and Millimeter Wave Sensing and Applications[END_REF]. OWC is one of the promising emerging alternative approaches which offers lots of advantages over RF transmission. As a subset of OWC, VLC is allowing the use of commercial LEDs for both illumination and data transfer operations. Owing to the widespread usage of such convenient illumination appliances, the interest in VLC technologies has multiplied in academia and industry. VLC uses an unregulated visible light spectrum between 380 nanometers and 780 nanometers with 670 Terahertz bandwidth for data transmission (see figure 2.4). With an unregulated huge band spectrum and the commercial LED, the implementation cost of VLC front-ends is low. In addition, VLC is free of any health concern as long as the eye safety regulations are respected [START_REF] Bsi British | Photobiological safety of lamps and lamp systems[END_REF]. Additionally, with the invention of precise PDs, VLC becomes a reliable candidate for medium-range data transmission that can contribute to addressing the RF shortage.

Figure 2.6 illustrates the major components of a generic VLC link. At the transmitter, the modulated digital information (bits, symbols) is transformed into the current signal and fed to the LED. LED converts the current signal to the information-carrier optical density. The optical signal may pass through an optical system in order to further shape the transmitted beam. For example, an optical amplifier lens concentrates or expands the beam. The optical signal is then transmitted over the optical wireless channel. A portion of the optical energy is absorbed by the objects in the surrounding, and the rest is reflected back in a diffuse or specular way. LoS and Non-LoS components of the transmitted signal get attenuated, fluctuated, and interfered in the OWC channel before arrival to the receiver. An optical filter can select a portion of interest from the received optical spectrum, and limit the interference from ambient lights [START_REF] Stephen | Optical Communication Receiver Design[END_REF]. The useful signal then can be amplified to be fed to the photodetector. At the photodetector, the optical signal is converted back to electrical current and post-processed to recover the information bits. In this process, the intensity Modulation and Direct Detection (IM/DD) should guarantee the real value and positive VLC signal. The most common single carrier intensity modulation techniques are listed in 2.5. The difference between the LoS and Non-LoS scenarios is twofold:

• The LoS kink neglects the multi-path dispersion.

• • Having a wide Field of View (FoV), the receiver at Non-LoS scenario accounts for surrounding surfaces dispersion At Non-LoS scenarios the receiver accounts for the dispersion from nearby surfaces

The sources of the distortions in VLC depend on the applying environment. For instance, in indoor applications, the major noise is coming from ambient lights such as fluorescent and incandescent lights, while sunlight is the primary noise concern in outdoor scenarios. The atmospheric fluctuation might be an important issue in outdoor applications depending on the weather condition. For example, fog is much more difficult to deal with, in comparison to rain and snow due to attenuation effects and discursive water particles in such climatic circumstances [START_REF] Mecklenbrauker | Vehicular Channel Characterization and Its Implications for Wireless System Design and Performance[END_REF].

Based on the aforementioned advantages and characteristics, VLC has a high potential to be employed in many applications. The application domains of VLC include indoor wireless communication, underwater communication, vehicular communications, positioning, and Machineto-Machine (M2M) communications [START_REF] Latif | Visible light communication: Applications, architecture, standardization and research challenges[END_REF]. LiFi: LiFi is a high-speed bidirectional visible light access point equivalent of WiFi. It can illuminate the living areas and offloads the data traffic from cellular networks simultaneously.

Underwater Communication, The propagation loss of the RF signal in the seawater is very high because of its conductivity. VLC has been used in the Un Tethered Remotely Operated Vehicle (UTROV) project for observatory maintenance deep in the oceans controlled from the ship on the sea level (See figure 2.7). Healthcare, In hospitals, the areas where electromagnetic waves are prohibited (e.g., where the MRI scanner is located) are likely to adopt VLC because it will not interfere with RF waves of traditional systems. Signalboard An array of modulated LEDs is used in the form of signboards in order to send the broadcasting information. Positioning, Accurate coordinates of a receiver is feasible using multiple VLC transmitters even in noisy environment [START_REF] Costanzo | Visible Light Indoor Positioning in a Noise-aware Environment[END_REF]. To carry out a precise positioning system using VLC, a receiver must pick up the signals from LEDs and calculate the distance from them. One algorithm for VLC positioning is to use Received Signal Strength (RSS) and count the Time of Arrival (ToA) in a synchronous way. Undoubtedly, VLC-based positioning applications going to be an important part of localization technologies in the near future [3]. Vehicular Communication, VLC can be used in vehicular communication owing to vehicle light and Road Side Unit (RSU) infrastructure. Vehicular VLC can support safety applications such as cooperative forward collision warnings, pre-crash sensing, emergency brake lights, lane change warnings, stop sign movement assistant, left turn assistant, traffic violation warning signal, and curve speed warnings. All of these safety applications, have some Quality of Service (QoS) requirements such as low latency, reliability and seamless connectivity [START_REF] Kim | Outdoor Visible Light Communication for inter-vehicle communication using Controller Area Network[END_REF]. Vehicular VLC is in the heart of this thesis and it deserves further explanations on its objectives, standards, mediums and challenges, therefore the following section is devoted to the details of V2LC.

V2LC

Vehicular communications enable a broad area of safety, environmental, and infotainment applications. The vehicular communication systems include vehicles and other communication entities around them such as RSU, clouds, grids and fog networks, the Internet, pedestrian smart devices, etc. The objective of vehicular communications is to ensure road safety, prevent road accidents, reduce fuel consumption and carbon emission, save time and offer a higher level of driving comfort. To reach these aims, information is exchanged among vehicles and other communication entities. This type of communication is called as the vehicle to everything (V2X) communication and it includes vehicle-tovehicle (V2V), vehicle-to-infrastructure (V2I), Vehicle-to-Network (V2N), vehicle-to-pedestrian (V2P), and Vehicle-to-Device (V2D) communication [START_REF] Weiß | V2X communication in Europe -From research projects towards standardization and field testing of vehicle communication technology[END_REF]. [25]. Mode-4 uses the PC5 interface at 5.9 GHz while Mode-3 uses the traditional LTE interface. In addition, Mode-3 depends on centralized scheduling, however Mode-4 is completely distributed. The purpose of direct communication between the vehicles (e.g., Mode-4) is to reduce the latency requirements, necessary in most of the time-critical ITS applications. The vehicles may switch between the desired modes dynamically. LTE has severe security vulnerabilities and other countermeasures that are discussed in detail in Chapter 5. 5G-New Radio (5G-NR) aims to provide higher data rates, lower latency, and multiple access communications among devices. The

V2LC Challenges

The exploitation of VLC as a transmission medium opened new horizons in communication systems and potentially promised to solve many issues associated with the wide range of applications, such as last-mile connectivity, positioning, and underwater communications. Since the time it came into being, VLC physical metrics such as data rate, and communication range grabbed the majority of the academic attention, while the Medium Access Control (MAC) issues, including network formation and handover, have been partially ignored mainly because the target application sector was for indoor environment [START_REF] Dimitrov | Principles of LED Light Communications: Towards Networked Li-Fi[END_REF].

Outdoor applications including Vehicular Communications (VC), have a great capacity to host VLC technology based on the already-existed infrastructures such as vehicles and road side units equipped with Light Emitting Diodes (LED) and cameras. However, V2LC has a number of challenges to be addressed: Hardware limitation: Hardware limitation of V2LC transmitters and receivers (e.g., nonlinearity of the electronic components) highly impact the achievable performance. Nonlinear transfer function, the limited bandwidth of the LEDs, and the limited dynamic range are some of the transmitter challenges in V2LC. On the receiver side, the "square law" property of the direct detection receiver and the noise induced by the hardware affect the communication [START_REF] Memedi | Vehicular visible light communications: A survey[END_REF].

A square law device produces an output proportional to the square of some input. For example, in demodulating radio signals, a semiconductor diode can be used as a square law detector, providing an output current proportional to the square of the amplitude of the input voltage over some range of input amplitudes.

Line of Sight, Propagation characteristics of the light and its directionality usually require an LoS link between the transmitter and the receiver in V2LC. Maintaining a stable LoS link under the dynamic mobility conditions of vehicular traffic is challenging in V2LC. In addition, in the outdoor environment, the light beams are not spatially bounded; when they are propagating, the reflected components cannot maintain sufficient energy for detection and reliable communication. Although an LoS link is preferred, initial research has shown that Non-LoS communication via ground reflections can be beneficial for V2LC. Nevertheless, this depends on the weather conditions and the ground surface material, as they impact the reflectivity of the ground. Regarding Non-LoS reflections, V2LC does not suffer from multi-path fading, because of the inherent spatial diversity resulting from the significantly shorter carrier wavelength of visible light waves compared to the detection area of typical receivers [START_REF] Tebruegge | Empirical characterization of the NLOS component for vehicular visible light communication[END_REF].

Outdoor Environment: Outdoor is a challenging environment for VLC. Atmospheric phenomena like fog, rain, snow, and other particles in the atmosphere, degrade the transmitted signal by absorbing and scattering the light waves. Similarly, dirt or dust around the lighting modules (or PDs) can hinder the signal. This will heavily influence the range and reliability of V2LC. The icing on the ground can cause stronger reflections too. Natural and artificial light sources impose a challenge for the system as well. Sunlight causes shot noise at the receiver, while outdoor LEDbased light sources (e.g., roadside illumination, advertisement boards) can cause interference [START_REF] Singh | Impact of Weather Conditions and Interference on the Performance of VLC based V2V Communication[END_REF]. Propagation Characteristics: VLC signals cannot penetrate through objects which are opaque to the human eye such as wood, metal, and plastic. As these materials are prevalent in our lives, the interaction of visible light wavelengths with those materials largely impacts the design decisions for VLC-based applications, including V2LC [START_REF] Memedi | Vehicular visible light communications: A survey[END_REF].

Directionality of Lighting Function:

The directionality of V2LC signals has governed by the design of the transmitter lighting modules and the Field of View (FoV) of the receiving PD. As a primary purpose, lighting modules for indoor or outdoor illumination are designed to provide optimal illumination in a certain area. In the case of automobile lights, the directionality of the light beams impacts many other properties of V2LC. For instance, it results in a small collision domain and allows high spatial reuse of the modulation bandwidth for devices in close proximity, and at the same time reduces the covered area [START_REF] Memedi | Vehicular visible light communications: A survey[END_REF]. Mobility: In the linear channel, the geometry between the sender and the receiver (i.e., relative distance and orientation) and the corresponding hardware characteristics (e.g., receiver's FoV and active collection area, transmitter's radiation pattern, etc) have the largest impact on the large-scale channel conditions [START_REF] Green | The optical wireless channel[END_REF]. The geometric parameters are mainly influenced by the vehicle's mobility, which, in turn, impacts the temporal characteristics of the channel. The optical channel, characterized by the Channel Impulse Response (CIR), does not change significantly if the transmitter-receiver pair move in the order of a wavelength. In the vehicular environment, however, typical displacements are orders of magnitude larger than the VLC wavelengths, making the V2LC channel highly dynamic [START_REF] Chen | Time variation in vehicle-to-vehicle visible light communication channels[END_REF].

Power Distribution: the most interesting property of V2LC is the imbalance of different lighting modules. For instance, as the headlamps and taillamps of a vehicle serve different purposes (e.g., illumination or signaling), there are significant differences in their design. Therefore, the light emitted by the headlamps is much stronger than the one emitted by the taillamps. This is resulting in an asymmetric link between two vehicles communicating with these lighting modules. Moreover, the light distribution of the headlight is not uniform. The idea is to illuminate more areas towards the curbside in order not to glare oncoming vehicles. These properties should be carefully taken into consideration when designing Medium Access Control (MAC) protocols for V2LC [START_REF] Memedi | Impact of Vehicle Type and Headlight Characteristics on Vehicular VLC Performance[END_REF].

In a nutshell, inter-vehicle communication at high relative speeds via V2LC may face the following key challenges: • resources management in high-density scenarios (random allocation of resources may result in excessive collisions), • • ensuring reliability for covered and uncovered communication. These issues need to be addressed in order to maintain the connectivity at a modest bitrate under the Line of Sight (LoS) constraints of VLC and rapid flexibility of VC, which in this study have been committed from the MAC layer perspective.

Previous Contributions

The early efforts on the VLC MAC layer back to 2003 in Japan where VLC Consortium sets basic protocols for VLC positioning and later on has been revised by IEEE 802.15.7 VLC Task Group to include Channel Sensing Multiple Access (CSMA) MAC protocol [3]. It is the same standard used by LiFi technology which supports indoor wireless networking systems including bi-directional multiuser communication [START_REF] Haas | What is LiFi?[END_REF]. Bi-directional VLC link was also adopted in [START_REF] Costanzo | Adaptive Modulation Control for Visible Light Communication Systems[END_REF], in order to implement the adaptive modulation control but in unfair uplink-downlink bandwidth. Essential differences between indoor and outdoor applications triggered prospective developments of the distinct models in VLC ad-hoc networks where infrastructure-less mobile nodes qualified to tackle network failures. However, the techniques used in this area were blindly drawn from RF networks such as aloha protocols [4][36]. In aloha, each node or station transmits a frame without trying to detect whether the transmission channel is idle or busy. If the channel is idle, then the frames will be successfully transmitted. If two frames attempt to occupy the channel simultaneously, collision of frames will occur and the frames will be discarded. These stations may choose to re-transmit the corrupted frames repeatedly until successful transmission occurs. In pure aloha, the time of transmission is continuous. Whenever a station has an available frame, it sends the frame. If there is collision and the frame is destroyed, the sender waits for a random amount of time before re-transmitting it. Slotted aloha reduces the number of collisions and doubles the capacity of pure aloha. The shared channel is divided into a number of discrete time intervals called slots. A station can transmit only at the beginning of each slot. However,there can still be collisions if more than one station tries to transmit at the beginning of the same time slot. J. Jagannath in [START_REF] Jagannath | An Opportunistic Medium Access Control Protocol for Visible Light Ad Hoc Networks[END_REF] presents an opportunistic medium access control protocol to counteract exclusive challenges of VLC ad-hoc networks such as hidden node, deafness and blockage. A three-way handshake mechanism has been proposed to negotiate medium access starting by choosing the optimal transmission sector which is the direction that maximizes the utility function. Utility function defined as a probability of establishing a duplex communication link when some of neighbor nodes are affected by blockage or deafness. Since full-duplex communication is inherent to VLC, the utility function boosts the establishment of full-duplex communication links. Hidden node problem has been met by full-duplex transmission or busy tone and power control implementation. All these factors contribute to maximizing the throughput of visible-Light ad-hoc network (LANET). J. Jagannath et al. have further elaborated VL-MAC to include a cross-layer optimized routing protocol (VL-ROUTE) that interacts closely with medium access control layer in order to maximize the throughput of the network by taking into account the reliability of the route. Route Reliability Score (RRS) computed by each node in the network using just the information gathered from its immediate neighbors, estimates the probability of reaching a given sink via that node.

The RRS value then integrated to the utility based three-way handshake process proposed in [START_REF] Jagannath | An Opportunistic Medium Access Control Protocol for Visible Light Ad Hoc Networks[END_REF] to mitigate the deafness, blockage and increase the chance of establishing a full-duplex links [START_REF] Jagannath | VL-ROUTE: A Cross-Layer Routing Protocol for Visible Light Ad Hoc Network[END_REF]. Opportunistic MAC protocol designed for VLC and based on three-way handshake [START_REF] Jagannath | An Opportunistic Medium Access Control Protocol for Visible Light Ad Hoc Networks[END_REF] are not able to follow the high dynamicity of a vehicular context. The performance of V2LC has been enhanced in atmospheric turbulence conditions by Aperture Averaging (AA) technique. AA uses a lens in front of PD to increase the collection area of the receiver so that the Signal to Noise Ratio (SNR) increases [START_REF] Eso | Performance of Vehicular Visible Light Communications under the Effects of Atmospheric Turbulence with Aperture Averaging[END_REF]. SNR is a well-known maximum received power indicator, with Gaussian noise distribution, even though overhearing the disturbances from other VLC transmitters offer less accurate performance evaluation. In [START_REF] Wu | Smart Handover for Hybrid LiFi and WiFi Networks[END_REF], the maximum received power has been used to make a soft horizontal handover among Coordinated Multi-Point (CoMP), by adjusting the handover power margin and time-to-trigger parameters. The Received Signal Intensity (RSI) extension in [START_REF] Vegni | Handover in VLC systems with cooperating mobile devices[END_REF] was inspired by the RF Received Signal Strength (RSS) concept, and exploited in the RSI-based handover technique for mobile VLC systems. Signal-to-interference and noise ratio (SINR) is used in [START_REF] Karbalayghareh | Channel Modelling and Performance Limits of Vehicular Visible Light Communication Systems[END_REF] to manage vertical handover between Li-Fi and Wi-Fi and to reduce the handover rate through the concept of handover skipping. The SINR evaluates the communication link more precisely, especially when the noise and interference power levels are comparable. Consequently, the interference is modeled as a Gaussian random process too, with finite independent signal aggregation, where no individual signal dominates over the rest, [START_REF] Win | A Mathematical Theory of Network Interference and Its Applications[END_REF]. At the same time, scenarios, where the disturbances are dominated by one or multiple sources, are commonly present in VLC systems. When the power of individual interferer or accumulative interference is at least one order of magnitude larger than the noise, the system is interference dominant. In this case, INR ought to properly describe the interference distribution [START_REF] Rahaim | Optical interference analysis in Visible Light Communication networks[END_REF], which was inspected as a Quality of Service (QoS) constraints for handover management in hybrid RF/VLC indoor systems [START_REF] Hammouda | Link Selection in Hybrid RF/VLC Systems Under Statistical Queueing Constraints[END_REF]. Post-Crash Notification as an example of safety messages has been disseminated through IEEE 802.11p assisted by VLC within the area of accident to prevent possible accumulation in platoon [START_REF] Ucar | Visible light communication assisted safety message dissemination in multiplatoon[END_REF].

As the main challenge for the LoS requirement is mobility, the mobile receiver in VLC has to maintain a high-speed connection in an uninterrupted manner within the coverage area of a single access point (AP), as well as when it is moving across multiple transmitters [START_REF] Haas | What is LiFi?[END_REF]. The principal solution for switching the communication session from one AP to another is the handover mechanism. The handover procedures are generally pushed by the degradation of the quality of the current link, followed by the selection of a higher quality host link (if there is any), and finally executing the handover through exchanging control packets among the nodes that share the link [START_REF] Dang | Handover Procedure and Algorithm in Vehicle to Infrastructure Visible Light Communication[END_REF]. The link quality evaluation is determined by the error probability ratio, which follows the distribution of the link disturbances such as noise and interference [START_REF] Rahaim | Optical interference analysis in Visible Light Communication networks[END_REF]. In the context of V2I communication, the street lights have served as access points and handover among them has been performed based on the coordinated multipoint algorithm, regardless of the vehicle velocity [START_REF] Demir | CoMP-Based Dynamic Handover for Vehicular VLC Networks[END_REF]. Handover techniques for V2X communication gained the major attention of this dissertation.

Conclusion

As the VLC is gaining more and more attention in academia and industry because of its capacity to complement RF technologies, new challenges raised when it is applied to outdoor applications. VC is one of the most interesting markets for VLC. V2LC guarantees fast data offloading in a reasonable cost. Meanwhile, mobility management and signal disturbances are the main issues against building a robust Vehicular Visible Light Communication. The most recent contributions to these challenges have been reviewed in this section, based on the historical developments of VLC. It is summed up with the most appropriate solution for node mobility in VLC outdoor environment.

Link Adaptive Protocol 3

Channel Model

As Visible Light Communications (VLC) is growing up, it is not restricted anymore to the traditional indoor applications such as LiFi and positioning, but it finds new customers at outdoor vendors like underwater and vehicular applications. Similar to any other communication system, the propagating channel limits the performance of the VLC system. The extensive studies that have been discussed in the last chapter, address the main challenges in indoor applications such as data rate. Those research restricted the channel impairments to the path loss. Path loss is reversely related to the distance between the transmitter and the receiver according to the Lambertian channel gain (i.e., 𝐻 𝐿𝑎𝑚 ). On the other hand, the performance of the outdoor VLC channel model has two signal attenuation factors: Sunlight shot noise via Lambertian radiation pattern and climate fluctuation model with atmosphere distortion index. The key elements of a generic outdoor VLC system are shown in figure 3.1. A Light emitting diode (LED) represents the transmitter, which transfers the optical power in the free space, while the photodetector (PD) as a receiver, generates an electrical current proportional to the optical received power. This communication scheme employs intensity modulation and direct detection (IM/DD). Elimination of local oscillators and broad employment of LEDs, nowadays, provides cost-effective infrastructure for communication services [START_REF] Dang | OFDM Systems for Optical Communication with Intensity Modulation and Direct Detection[END_REF]. Intensity modulation assures non-negative instant emitted optical signal X(t) between minimum and maximum signal power as:

𝑢 ≤ 𝑋(𝑡) ≤ 𝑈, with average transmit power (i.e., 𝑃 𝑡 ) equivalent to the expected value of the emitted optical power 𝐸(𝑋) [START_REF] Aldalbahi | Visible Light Communication Module: An Open Source Extension to the ns3 Network Simulator With Real System Validation[END_REF]. Instant received optical signal can be modeled as 3.2:

𝑌(𝑡) = 𝑟𝑋(𝑡) ⊗ ℎ(𝑡) + 𝑁(𝑡) (3.2)
Here, 𝑟 represents the photodetector responsivity, and ℎ(𝑡) describes the outdoor optical channel impulse response (CIR), taking into account the Lambertian path loss ℎ 𝐿𝑎𝑚 and statistical climate impairments ℎ 𝑐𝑙𝑚 model [START_REF] Lin | Outage performance analysis for outdoor vehicular visible light communications[END_REF]. In 3.2, 𝑁(𝑡) stands for the Additive White Gaussian Noise (AWGN), and ⊗ is the convolution operator.

The average received power represented by 3.3:

𝑃 𝑟 = ℎ • 𝐸(𝑋) (3.3)

Channel Gain

At the indoor line of sight (LoS) condition, the channel model is restricted to the Lambertian emission of order 𝑚, and formulated as 3.4:

ℎ 𝐿𝑎𝑚 = (𝑚 + 1)𝐴 2𝜋𝑑 2 cos 𝑚 (𝜙)𝑇 𝑠 (𝜓)𝑔(𝜓) cos(𝜓) (3.4)
being 𝑚 the order of Lambertian emission, it is calculated as 3.5:

𝑚 = -ln(2)/ln cos 𝜙 1/2 (3.5)
𝜙 1/2 stands for the half-power semi-angle at the transmitter, the photodetector area is 𝐴, and 𝑑 indicates the distance between the transmitter and the receiver. Based on figure 3.2, the angle of radiance and acceptance identified by 𝜙 and 𝜓 respectively and 𝑇 𝑠 (𝜓) is optical filter gain. The concentration gain of the photodetector (i.e., 𝑔(𝜓)) ruled by 3.6 with 𝑛 refractive index and 𝜓 𝑐 receiver field of view (FoV) [START_REF] Komine | Fundamental analysis for visible-light communication system using LED lights[END_REF]. Outdoor VLC channel on the other hands, suffers from additional climate distortion (i.e., ℎ 𝑐𝑙𝑚 ), statistically modeled as 3.7 with log-normal Probability Density Function (PDF) of climate distortion 𝑓 ℎ 𝑐𝑙𝑚 and log-amplitude variance 𝜎 2 𝐿 determined through ray tracing analysis [START_REF] Karbalayghareh | Channel Modelling and Performance Limits of Vehicular Visible Light Communication Systems[END_REF].

𝑔(𝜓) = 𝑛 2 sin 2 𝜓 𝑐 , 0 ≤ 𝜓 ≤ 𝜓 𝑐 0 , 𝜓 ≥ 𝜓 𝑐 (3.6)
ℎ = ℎ 𝐿𝑎𝑚 • ℎ 𝑐𝑙𝑚 (3.7) 𝑓 ℎ 𝑐𝑙𝑚 (ℎ 𝑐𝑙𝑚 ) = exp (ln(ℎ𝑐𝑙𝑚)+2𝜎 2 𝐿 ) 2 8𝜎 2 𝐿 2ℎ 𝑐𝑙𝑚 2𝜋𝜎 2 𝐿 (3.8)

Noise model

The dominant part of the noise in outdoor applications is due to the daylight shot noise rather than other ambient interference sources like incandescent or fluorescent lamps. Encountering thermal noise as the other major noise source, the total noise variance (i.e., 𝜎 2 𝑛 ) will be like 3.9:

𝜎 2 𝑛 = 𝜎 2 𝑠 ℎ𝑜𝑡 + 𝜎 2 𝑡 ℎ𝑒𝑟𝑚𝑎𝑙 (3.9)
Shot noise variance and thermal noise variance derived from 3.10 and 3.11.

𝜎 2 𝑠 ℎ𝑜𝑡 = 2𝑞𝑟𝐵(𝑃 𝑟 + 𝐼 2 𝑃 𝑏 𝑔 ) (3.10) 𝜎 2 𝑡 ℎ𝑒𝑟𝑚𝑎𝑙 = 8𝜋𝑘𝑇 𝑘 𝜂𝐴𝐵 2 ( 𝐼 2 𝑔 𝑚 + 2𝜋Γ𝜂𝐴𝐼 3 𝐵𝐺 𝑔 𝑚 𝐺 ) (3.11)
Background noise power (i.e., 𝑃 𝑏 𝑔 ) is estimated as 3.12:

𝑃 𝑏 𝑔 = 0.0079𝐸 𝑑𝑒𝑡 𝑇 0 𝐴𝑛 2 (3.12)
Table 3.1 is associated with illuminance range (i.e., 𝐸 𝑑𝑒𝑡 ) of the ambient light [START_REF] Fields | Correlation of objectively measured light exposure and serum vitamin D in men aged over 60 years[END_REF], and table 3.2 contains the parameters used in the current model with their values.

Link Adaptive Protocol

The link adaptive protocol makes a quick connection when a VLC link is available, adjusts the data rate based on the quality of the link, and

𝑆𝑁 𝑅 = (𝑟𝑃 𝑡 ℎ) 2 𝜎 2 𝑛 (3.13)
After each pilot window (i.e., 𝑇 𝑝 ), the maximum value of the SNR is derived, and once the maximum signal to noise ratio surpasses the threshold (i.e., 𝑀 𝑎𝑥 𝑆𝑁 𝑅 ≥ 𝛼), the source of that signal will be nominated for the association, otherwise, the scanning phase relaunches. 𝛼 initially set as the minimum SNR required to achieve a given quality of service(QoS) in terms of reliability (i.e., 𝐵𝐸𝑅).

In the association phase, the source sends an association request to the destination and waits for the association response on the same link. If the association has been accepted before the timeout, it passes to the transmission phase. If not, the scanning phase starts again. Finally, the transmission initiates and is maintained among different modulation schemes based on modulation table 3.3, unless the link quality factor 𝐸 𝑏 /𝑁 0 drops below the threshold. Since then, the scanning step restarts.

Simulation

As the majority of VLC research focused on the optimization of the physical medium, the cumbersome issue was to find a robust tool to evaluate the system performance in realistic situations. Current network simulators such as OMNeT++, ns2, and ns3 has limited evaluation support for VLC networks. This has motivated our work, to develop a VLC module within ns3 which offers an open-source network-level VLC simulator. NS-3 is a discrete-event network simulator for Internet systems, targeted primarily for research and educational use. NS-3 is free, open-source software, licensed under the GNU GPLv2 license, and maintained by a worldwide community [START_REF]ns3 Network Simulator[END_REF]. We extended the "ns3-V2LC" module from

The motivations behind choosing ns3 to implement our system model are as follows:

• the number of ns3 users is increasing [START_REF]ns3 statistics[END_REF] • It is open source and free ℎ 𝑐𝑙𝑚 [START_REF] Lin | Outage performance analysis for outdoor vehicular visible light communications[END_REF]. Moreover, it accounts for the delay, propagation loss, and sumo trace source.

Performance model

The link performance of different modulation schemes such as VPPM, PAM, OOK, and PSK is evaluated in terms of signal to noise ratio and the quality of service metric (i.e., BER, and SER).

Mobility model

The mobility model parses the coordinates of the mobile nodes from SUMO in addition to the velocity vector and other mobility parameters in real-time. it includes urban and highway scenarios.

Performance Analysis

A generic scenario, shown in Figure 3.5, has been arranged in a way to include association, adaptive modulation and handover algorithms using NS3-V2LC module [START_REF] Aldalbahi | Visible Light Communication Module: An Open Source Extension to the ns3 Network Simulator With Real System Validation[END_REF]. Mobile node1 rides for 20 meters, passing by node2 and node3, each of which is equipped with the VLC front-end of Figure 3.1. Simulation parameters are provided in Table 3.2.

Fixing the maximum error probability for safety applications equal to 10 -5 we derive 𝛼 = 11.5[𝑑𝐵] from Figure 3.6 and accordingly construct the modulation table 3.3 [START_REF] Song | Performance Analysis of the IEEE 802.11p Multichannel MAC Protocol in Vehicular Ad Hoc Networks[END_REF]. As a result, node1 associates with node2 as soon as 𝑆𝑁 𝑅 𝑚𝑎𝑥 exceeds 11.5𝑑𝐵 and goes to the transmission phase. Node1 starts transmission with the minimum modulation level (OOK) and as it is approaching node2, the modulation level upgrades based on modulation table 3.3. When node1 traverses node2, the received power from node2 starts to decrease, and consequently, the modulation level degrades relatively until the SNR drops below the threshold. Here node1 goes to the scanning phase where it finds the signal quality of node3 is In order to evaluate the performance of the LAP, an analytical comparison with slotted aloha has been performed based on outage probability and the data rate. Additionally, the protocol efficiency has been examined as a function of pilot frequency 𝑓 𝑃 . Pilot frequency is the rate of broadcasting an exploring pilot message.

Outage probability is the Gaussian Q-function of SNR when it drops below the threshold [START_REF] Lin | Outage performance analysis for outdoor vehicular visible light communications[END_REF] and can be modeled as follows (3.14):

𝑃 𝑜𝑢𝑡 = 𝑃𝑟𝑜𝑏(𝑆𝑁 𝑅 ≤ 𝛼) = ∫ ℎ min 0 𝑓 (ℎ)𝑑ℎ (3.14)
Where 𝑓 (ℎ) is the joint probability density function of the climate and path loss distortion, it is formed thereby (3.15) :

𝑓 (ℎ) = 1 ℎ 𝐿𝑎𝑚 𝑓 ℎ 𝑐𝑙𝑚 ℎ ℎ 𝐿𝑎𝑚 (3.15)
According to 3.4, minimum channel gain ℎ min is the channel gain at maximum transmission range 𝑑 max where 𝛼 fulfills.

ℎ min = (𝑚 + 1)𝐴 2𝜋𝑑 2 max cos 𝑚 (𝜙)𝑇 𝑠 (𝜓)𝑔(𝜓) cos(𝜓) (3.16)
Properly using (3.7) to (3.8), 𝑃 𝑜𝑢𝑡 is simplified as 3.17:

𝑃 𝑜𝑢𝑡 = 𝑄        - ln ℎ min ℎ 𝐿𝑎𝑚 + 2𝜎 2 𝐿 2𝜎 𝐿        = 𝑄        - ln 𝑑 2 𝑑 2 max + 𝜎 2 𝐿 𝜎 𝐿        (3.17)
Figure 3.7 represents the outage probability in respect of the relative distance between the front-end transmitter and the receiver. For the sake of comparison, the slotted aloha channel accessing model has been implemented with different modulation schemes namely: on-off keying (OOK), Variable PPM (VPPM) with 0.6 duty cycle, Quadrature Amplitude Modulation (QAM) and phase shift keying with 16 modulation levels. Based on the figure 3.7 the link adaptive protocol (LAP) is outperforming the slotted aloha outage probability with VPPM, 16QAM, and 16PSK modulation schemes while it coincides with the performance of slottedaloha with OOK modulation scheme. In the other words, the LAP adapts the transmission scheme to the best of channel quality such that when the distance between the transmitter and the receiver is high (i.e., above 2.5 m), it uses the most robust modulation scheme (i.e., OOK) for transmission in order to increase the coverage range in the charge of the data rate.

To assess the adaptive modulation algorithm, the goodput has been defined as the rate of delivered data to the application layer discarding all the overheads represented in 3.18, where 𝜁 is the number of good packets received with payload 𝑝 per transmission period 𝑇.

𝑔𝑜𝑜𝑑𝑝𝑢𝑡 = 8 • 𝑝 • 𝜁 𝑇 (3.18)
As it is visible in Figure 3.8, LAP goodput is improved proportionally to the signal quality while the goodput of slotted-aloha remains unchanged regardless of increasing the SNR albeit the more complicated modulation scheme results in higher goodput. It means, the LAP is capable to deliver The goodput of the link adaptive protocol depends on the system's awareness of the received signal evolution. The earlier the signal alteration is detected, the faster the modulation adapts. A common technique to raise system awareness is exploring the VLC environment more often. The ideal case happened when the system is able to adapt the transmission criteria to the link condition continuously (i.e., 𝑓 𝑃 → ∞).

Figures 3.9 and 3.10 represent the effects of pilot frequency augmentation on the goodput when SNR increases, compared to the ideal case with different velocities. According to these figures when the pilot frequency increases, the LAP curves get closer to the ideal case meaning that it adapts faster to the link condition. Moreover, the adaptation sensitivity depends on the velocity of the mobile device too. At higher speeds, the adaptation sensitivity is higher which requires higher pilot frequency to keep the same performance as the lower speed.

The very direct benefit of rapid adaptation to the channel condition is the enhancement of the throughput, which is obvious in figure 3.11. However, increasing the pilot rate (i.e., 𝑓 𝑃 )imposes more overhead on Increasing the inquiry messages (i.e., pilot), enhance the Channel State Information (CSI) and as a result increase the throughput the network according to to figure 3.12 which in consequence, reduces the protocol efficiency according to 3.19, and is shown in figure 3. 13.

𝜂 𝑝 = delivered traffic delivered traffic + overhead (3.19)
Increasing pilot frequency imposes more overhead to the system which reduces the protocol efficiency

Conclusion

This chapter addresses the challenges raised in VLC outdoor applications in terms of connectivity and throughput by means of Link Adaptive Protocol. A new ns3-based module has been proposed to implement the channel model. The frequent scanning, tactile association, and flexible transmission assure lower outage probability and high goodput in comparison to slotted-aloha. Last but not least, a trade-off between protocol efficiency and pilot frequency has been investigated. Based on our findings, higher investigation rate is beneficial for the throughput, however, it reduces the system efficiency. Moreover, an experimental validation was carried out through a softwaredefined approach, considering a small-scale scenario and low-power LEDs. A perfect results alignment between simulation and measurement shows how the suggested INR-based mechanism overcomes classical SNR-based handover for all performance parameters evaluated in this study.

Interference-Based

V2LC Handover

The growing number of mobile devices and their applications enforce a huge amount of data exchange, pushing radio frequency-based wireless technologies to their resources limit. New paradigms, such as visible light communication (VLC), are appeared to complement RF technologies in addressing the spectrum crunch. VLC exploits pre-existing infrastructures like Light Emitting Diodes (LEDs), in order to provide not only illumination but also to transfer data. Plenty of indoor and outdoor VLC applications have emerged in the last decade, including LiFi, localization, and underwater communications. Intrinsic security due to limited penetration depth and a huge bandwidth of totally free spectrum are the other key factors behind the growing interest in VLC [3] [58] [34] [START_REF] Vegni | A VLC-based Footprinting Localization Algorithm for Internet of Underwater Things in 6G networks[END_REF].

Vehicular Visible Light communication (V2LC) represents one of the most attractive outdoor applications of this paradigm. The aim of V-VLC is to enhance the safety and driving experience by exchanging information between a generic vehicle and its surrounding (e.g., Vehicle-to-Vehicle V2V, Vehicle-to-Infrastructure V2I) using car lamps, traffic lights, control cameras and so on. However, like the other outdoor VLC techniques, advances in V-VLC are slower compared to indoor VLC, mainly due to environmental issues (e.g., sunlight noise, weather conditions, and higher mobility) [5].

In absence of ambient disturbances, VLC link quality depends on the distance between the transmitter and the receiver and their orientation in addition to the front-end configuration (i.e., field of view FOV of the receiver, area of the photodiode PD and radiation pattern). If the relative movement between the transmitter and the receiver is in the order of the signal wavelength, the quality of the optical channel represented by the channel impulse response (CIR) does not change significantly, therefore it has a minor impact on the temporal characteristics of the channel [START_REF] Green | The optical wireless channel[END_REF].

In vehicular communication, however, the transmitter-receiver motion is several orders of magnitude larger than the optical wavelength, which makes the V-VLC channel unstable [START_REF] Cheng | Comparison of Radio Frequency and Visible Light Propagation Channels for Vehicular Communications[END_REF]. Directional and line of sight (LoS) necessities of the VLC channel, further complicate the mobility management in the V-VLC context [START_REF] Dang | Handover Procedure and Algorithm in Vehicle to Infrastructure Visible Light Communication[END_REF]. A principal solution for mobility management is handover, where the Mobile Entity (ME) has to switch its communication session to another Access Point (AP) in the same network (horizontal handover) or to another technology (vertical handover). An effective handover is important as well to meet the quality of service (QoS) requisites (e.g., reliability, delay). The handover procedure is generally carried out in three steps: decision, target-AP/technology selection, and execution. In the handover decision, the ME decides to switch from the current AP to another candidate according to the quality of the link [START_REF] Dang | Handover in outdoor Visible Light Communication system[END_REF]. If there are multiple candidates, the ME has to select one of them, and finally, handover execution takes place via exchanging control packets between the ME and the candidate AP.

By reference to the previous works in the context of V-VLC, handover is generally based on the link quality which is evaluated by the signalto-noise ratio (SNR), mainly considering in the analysis, the presence of Gaussian noise (i.e., shot noise and thermal noise) [START_REF] Rahaim | Optical interference analysis in Visible Light Communication networks[END_REF].

In the dynamic soft handover algorithm, the coordinated multipoint (CoMP) is implemented according to the rate of change in the maximum received power to adjust handover parameters such as handover margin and the time-to-trigger [START_REF] Demir | CoMP-Based Dynamic Handover for Vehicular VLC Networks[END_REF]. However, the evaluation of the system by observing only the SNR and ignoring any disturbances from other transmitters does not provide an accurate performance evaluation [START_REF] Dang | Handover in outdoor Visible Light Communication system[END_REF]. Signal-to-interference and noise ratio (SINR) is also employed in handover decisions, since it provides higher precision compared to SNR, especially when noise and interference power levels are in the same order of magnitude. In this case, the interference is modeled as a Gaussian random process too, considering the accumulation of many independent signals where no individual signal dominates over the others [START_REF] Win | A Mathematical Theory of Network Interference and Its Applications[END_REF].

Handover skipping could reduce the handover rate in hybrid LiFi-WiFi networks by implementing Reference Signal Received Power (RSRP) for vertical handover and SINR for horizontal handover [START_REF] Wu | Smart Handover for Hybrid LiFi and WiFi Networks[END_REF]. Nevertheless, a dominant interferer is present in many real scenarios. In this case, a more accurate way to describe the interference distribution is by utilizing the interference to noise ratio (INR) [START_REF] Rahaim | Optical interference analysis in Visible Light Communication networks[END_REF].

In the next section, we employ the INR as the main metric for handover procedures. We consider both Gaussian interference distribution, and dominant interferer distribution, but we select which of them is applied, on the basis of interferer-to-interference ratio (IIR). Moreover, target AP selection is made based on the QoS requirements of the vehicular application. In order to achieve further improvement in overall system performance, the adaptive modulation scheme (AMS), dynamically switching between On-Off Keying (OOK) and Phase Shift Keying (PSK) Modulation with a different order (4-8-16 PSK), has been implemented.

System model

As illustrated in figure 4.1, we consider a V2LC architecture, composed of street lights, acting as APs and randomly distributed along the direction of the road with a linear distribution density 𝜌 𝑙 , defined as the number of APs per kilometer. Each AP has a maximum transmission range 𝑑 𝑚𝑎𝑥 , which depends on the VLC front-end configuration and the optical channel, whose transfer function (ℎ) is characterised by the Lambertian emission (ℎ 𝑙𝑎𝑚 ) and the climate loss (ℎ 𝑐𝑙𝑚 ) (see equation 4.1).

ℎ = ℎ 𝑙𝑎𝑚 ℎ 𝑐𝑙𝑚 (4.1)
The climate loss is statistically related to the variance of the amplitude and modeled by the ray tracing analysis [START_REF] Karbalayghareh | Channel Modelling and Performance Limits of Vehicular Visible Light Communication Systems[END_REF]. Under LoS constraint, the channel model is restricted to the Lambertian model [START_REF] Lin | Outage performance analysis for outdoor vehicular visible light communications[END_REF]:

ℎ 𝐿𝑎𝑚 = (𝑚 + 1)𝐴 2𝜋𝑑 2 cos 𝑚 (𝜙)𝑇 𝑠 (𝜓)𝑔(𝜓) cos (𝜓) (4.2)
Where 𝑚 is the order of Lambertian emission, 𝐴 is the area of the photodiode PD, 𝑑 is the distance between the ME and the AP. 𝜙 and 𝜓 are the angles of radiance and acceptance respectively, and the optical filter gain is represented by 𝑇 𝑠 . 𝑔 is photodetector concentrator gain. The main loss in the outdoor applications of VLC is due to daylight shot noise and thermal noise which are assumed to be Gaussian distributed with respective variances 𝜎 2 𝑠 ℎ𝑜𝑡 and 𝜎 2 𝑡 ℎ𝑒𝑟𝑚𝑎𝑙 . Given independent noise sources, the central limit theorem is applied to find the variance of the aggregate noise current (i.e., 𝜎 2 𝑛 ) as 4.3 The SNR provides an accurate optical link evaluation when the system is Gaussian noise dominant.

𝜎 2 𝑛 = 𝜎 2 𝑠 ℎ𝑜𝑡 + 𝜎 2 𝑡 ℎ𝑒𝑟𝑚𝑎𝑙 (4.3)
𝑆𝑁 𝑅 = (𝑟 • 𝑃 𝑟 ) 2 𝜎 2 𝑛 , (4.4)
In (4.4), 𝑟 represents the PD responsivity and 𝑃 𝑟 stands for the average received optical power. In an interference-dominant network, where the sensor is affected by the neighboring transmitters, an accurate performance analysis requires the evaluation of the interference and the noise jointly.

System interference is frequently modeled as a Gaussian random process since it is assumed no individual signal dominates [START_REF] Win | A Mathematical Theory of Network Interference and Its Applications[END_REF]. In such scenarios the variance of the aggregate interference current (i.e. 𝜎 2 𝐼 [𝐴 2 ]) is used to define signal-to-interference ratio (𝑆𝐼𝑅) evaluation of the link between the transmitter and the receiver i.e. 4.5,

𝑆𝐼𝑅 = (𝑟 • 𝑃 𝑟) 2 𝜎 2 𝐼 , (4.5)
Performance evaluation of the Tx-Rx link when the disturbances from both noise and interference are in the same order of magnitude is feasible through 𝑆𝐼𝑁 𝑅 (i.e., 4.6)

𝑆𝐼𝑁 𝑅 = (𝑟 • 𝑃 𝑟 ) 2 𝜎 2 𝐼 + 𝜎 2 𝑛 , (4.6)
These assumptions are not precise when the dominant interferer is present. In such scenarios, the interference is properly modeled by the distribution of the dominant interferer [START_REF] Rahaim | Optical interference analysis in Visible Light Communication networks[END_REF]. In order to determine if a dominant interferer is present, one can define the interferer to interference ratio as 4.7

𝐼𝐼𝑅 = max 𝑖 𝑃 𝑟,𝑖 Σ 𝑖≠𝑠 𝑃 𝑟,𝑖 , (4.7)
where the useful signal 𝑠 is not included within the interferers 𝑖. Lower IIR values fit well with the Gaussian distribution [START_REF] Rahaim | Optical interference analysis in Visible Light Communication networks[END_REF], while high values of IIR exclude this hypothesis. In fact, if IIR is greater than 𝛽, we consider that the interference distribution follows the dominant interferer. 𝛽 statistically defines the minimum IIR the system can be detected. Once this aspect has been determined (interference dominated or not), one can rely on the appropriate metric in order to evaluate the quality of the link.

In our system, the total interference to noise ratio 𝐼𝑁 𝑅 𝑡 is calculated as 4.8:

𝐼𝑁 𝑅 𝑡 = 𝑖≠𝑠 𝐼𝑁 𝑅 𝑖 , (4.8)
where the 𝐼𝑁 𝑅 𝑖 is the interference to noise ratio of the 𝑖 𝑡 ℎ interferer. Link performance evaluation depends on the QoS required by the application. One of the essential QoS requirements is the reliability described as the BER-SNR curve. Fixing the maximum error probability for vehicular safety applications equal to 10𝑒 -3, the minimum required signal to noise ratio (𝛼) is shown in In order to increase the lifetime of the link, the vehicle should avoid unnecessary handovers [START_REF] Safa | An Intelligent Vertical Handover Scheme for Audio and Video Streaming in Heterogeneous Vehicular Networks[END_REF]. Skipping unnecessary handovers will reduce the handover rate. The handover is unnecessary if the sojourn time 𝑡 𝑠 is shorter than connection lifetime 𝑇 𝑐 which is the other important QoS requirement for lots of applications. Sojourn time is defined as the time estimated for the ME to be served by a given AP (4.10):

𝑡 𝑠 = 𝑑 𝑚𝑎𝑥 + (𝑋 𝑀𝐸 -𝑋 𝐴𝑃 ) 𝑉 𝑀𝐸 (4.10)
where X and V are the position and the velocity vectors respectively. Putting these conditions together, the dominant interferer will be candidate as an AP if 𝐼𝑁 𝑅 𝑖 ≥ 𝛼 and 𝑡 𝑠 ≥ 𝑇 𝑐 . This process will be successively reapplied if there are multiple dominant interferers.

Simulation Analysis

In this section, we compare the INVISIBLE handover mechanism with the SNR-based handover as a benchmark scheme described in algorithm 3. For the sake of fairness, we applied the AMS on top of both handover mechanisms using the NS3 simulation tool [START_REF] Aldalbahi | Extending ns3 to simulate visible light communication at network-level[END_REF]. The main simulation parameters are shown in table 4.2.

Algorithm 3 SNR-based handover

Require: 𝑠, 𝛼, 𝑇 𝑐 , 𝑡 𝑖 𝑆𝑁 𝑅 = max 𝑖≠𝑠 (𝑟𝑃 𝑟,𝑖 ) 2 𝜎 2 𝑛 if 𝑆𝑁 𝑅 ≥ 𝛼 then 𝑡 𝑠 = 𝑑 𝑚𝑎𝑥 +(𝑋 𝑀𝐸 -𝑋 𝐴𝑃 ) 𝑉 𝑀𝐸 if 𝑡 𝑠 ≥ 𝑇 𝑐 then 𝑇 𝑐 = 𝑡 𝑠 𝑠 = 𝑖 end if end if if null then backoff 𝑡 𝑖 end if
The HO rate of the proposed handover mechanism is illustrated in figure 4.2 with two speeds and compared to the SNR-based handover algorithm. Considering the same AP density, the higher the speed, the shorter the average sojourn time and therefore, the higher the handover rate (4.11): In figure 4.3, we assess the impact of the AP density on the average delivered data per handover, considering the slow speed of the vehicles, equal to 25 Kmph and a rapid gait equal to 100 Kmph. The average delivered data per handover is the total amount of delivered data over the total number of handovers. Since in the proposed mechanism, the transmission takes place only under good coverage of a given AP (based on QoS requirement), as the speed increases, the sojourn time decreases, reducing the useful time to transmit and deliver data. In a given velocity, with sparse AP distribution (low AP density), the amount of delivered data per handover is higher, not because we delivered more data (because we delivered almost the same amount of data when we are connected to a given AP) but because the total number of handover is less in both schemes.

𝐻𝑂 𝑟𝑎𝑡𝑒 = 1 𝑡 𝑠 × 60
As the AP density grows, both the amount of delivered data and the number of handover increase, but the number of handovers grows faster than the amount of delivered data, therefore the overall ratio goes down. On the other side, an interference-based handover mechanism delivers almost the same amount of data by much lower number of handovers.

In the other words, signal-based handover mechanism performs many unnecessary handovers which degrade its performance compared to the interference-based mechanism.

Handover delay is a vital parameter to assess the time efficiency of performing a handover [START_REF] Dang | Handover Procedure and Algorithm in Vehicle to Infrastructure Visible Light Communication[END_REF]. Regarding the handover delay, the time efficiency of a given handover mechanism is defined as the time required for performing the handover(𝐻𝑂 𝑑𝑒𝑙𝑎𝑦 ) to the whole connection time offered by that handover (𝑡 𝑠 ) [START_REF] Dang | Handover in outdoor Visible Light Communication system[END_REF] i.e., (𝑀) ). Given the modulation scheme 𝑀 (𝑀 ∈ {𝑂𝑂𝐾, 4𝑃𝑆𝐾, 8𝑃𝑆𝐾, 16𝑃𝑆𝐾}) and 𝑅 𝑏,𝑡𝑥 (𝑀) = 𝑅 𝑏,𝑟𝑥 (𝑀) the handover request time is simplified through eq. (4.14),

𝐻𝑂
𝑡 𝐻𝑂 𝑟𝑒 𝑞 (𝑀) = 2 𝐻𝑂 𝑓 𝑟𝑎𝑚𝑒 𝑠𝑖𝑧𝑒 𝑅 𝑏,𝑡𝑥 (𝑀) (4.14)
The average handover time is calculated as follows:

𝑡 𝐻𝑂 𝑟𝑒 𝑞 = 𝑀 𝑡 𝐻𝑂 𝑟𝑒 𝑞 (𝑀) • 𝐻𝑂 𝑟𝑎𝑡𝑒 (𝑀) 𝐻𝑂 𝑟𝑎𝑡𝑒 , (4.15)
where 𝐻𝑂 𝑟𝑎𝑡𝑒 (𝑀) is the handover rate on the modulation scheme 𝑀. The evolution of the handover delay ratio compared to the AP density, for 25Kmph and 100Kmph, is shown in figure 4.5. For different speeds, the average sojourn time 𝑡 𝑠 is different while the average handover delays 𝑡 𝐻𝑂 is constant. The higher the speed the lower the sojourn time and as a consequence the higher the HO delay ratio. This ratio weakly increases in the interference-based handover mechanism, however in the SNR-based handover scheme this ratio shows faster progress. For low AP density, the performance of the signal-based HO is better because the HO frame size of SNR based is shorter than the interference-based handover frame size while both schemes perform the same number of handovers. When the AP density increases, the interference-based handover substantially outperforms the SNR-based handover, as it compensates for the higher overhead with a lower handover rate.

Small-scale Implementation

In this section, we implement in smaller scales the INR-based handover mechanism and compare it to the benchmark scenario (SNR-based). To verify how much the simulation results are close to the real scenarios we repeated the same procedures however downscaling the distances and the velocities to match our working environment. The communication system is evaluated at 0.15 𝑚𝑝𝑠 and 0.3 𝑚𝑝𝑠 velocities for different parameters i.e., handover rate, delivered data per handover, and handover delay ratio, through an extensive simulated campaign. Experimental validation was carried out through a software-defined approach, considering a small-scale scenario and low-power Light Emitting Diodes (LEDs). A perfect results alignment between simulation and measurement shows how the suggested INR-based mechanism overcomes classical SNR-based handover for all performance parameters evaluated in this study.

The mobile node (𝑃𝐷) in Figure 4.6 is crossing multiple VLC coverage areas while moving along 𝑥 -𝑎𝑥𝑖𝑠. The quality of the link degrades as it moves away from a fixed AP (LED i) due to the path loss and the front-end orientation. In order to maintain the connectivity link with a predefined Quality of Service (QoS) level, the receiver 𝑃𝐷 may assess the link quality frequently (i.e. every 𝑡 𝑖 seconds) and modify the transmission parameters, if required . The INR-based algorithm (1) evaluates the link performance based on the prominent component of the disturbances. To this end, it starts with a 𝐼𝑁 𝑅 calculation to determine if the system is noise-dominant or interference-dominant. In order to consider the system interference dominant, the interference power must be 10 times bigger than the noise power. In case 𝐼𝑁 𝑅 < 10, the noise and the interference power are comparable, and we treat them equally as noise.

At the interference dominant system, there could be single or multiple dominant interferers. The IIR is able to identify the dominant interferer if the IIR value is bigger than a threshold 𝛽, which is the minimum amount of IIR the system can detect and it is experimentally selected according to the node density(𝜌 𝑙 ). The interferers with 𝐼𝐼𝑅 ≤ 𝛽 are not dominant and are considered as noise. The dominant interferer 𝑖 with 𝐼𝐼𝑅 ≥ 𝛽 will be nominated for handover if it satisfies the QoS requirements of safety applications, expressed in terms of reliability and stability.

A reliable link has 𝑆𝑁 𝑅 𝑖 ≥ 𝛼 [dB], where 𝛼 is the minimum SNR level required for safety applications at maximum error probability, equal to 10 -3 [START_REF] Song | Performance Analysis of the IEEE 802.11p Multichannel MAC Protocol in Vehicular Ad Hoc Networks[END_REF].

In order to increase the lifetime of a single link, the mobile node should avoid unnecessary handovers [START_REF] Safa | An Intelligent Vertical Handover Scheme for Audio and Video Streaming in Heterogeneous Vehicular Networks[END_REF]. Skipping unstable VLC sessions will increase the connection time i.e., 𝑡 𝑠 [s], estimated as 4.10. Setting the minimum required connection time equal to 𝑇 𝑐 [s], the dominant interferer 𝑖 will be candidate as AP if 𝐼𝑁 𝑅 𝑖 ≥ 𝛼 and 𝑡 𝑠 ≥ 𝑇 𝑐 . This process will be successively reapplied in case of multiple dominant interferers. Finally, the dominant interferer 𝑖 with the maximum connection time is returned to adaptive modulation scheme, as explained in Algorithm 2.

On top of the handover mechanism, an Adaptive Modulation Scheme (AMS) protocol triggers different modulation schemes based on Table 4.3, in order to obtain a proper compromise between the data rate and the communication robustness. The relative bitrates are appropriately selected at the simulator to cope with the testbed limited components. After co-channel interference mitigation among different LEDs using frequency division multiplexing [START_REF] Costanzo | Visible Light Indoor Positioning in a Noise-aware Environment[END_REF], the proper modulation scheme is used for transmission, while the low 𝑆𝑁 𝑅 𝑖 amount requires a handover decision.

𝛼

Experimental Validation

The proposed INR-based protocol for transmission and handover has been implemented in NS3 simulator [START_REF] Aldalbahi | Visible Light Communication Module: An Open Source Extension to the ns3 Network Simulator With Real System Validation[END_REF] as well as a real small-scale scenario for proper experimental validation. In particular, we compare simulated and experimental protocol performance in terms of • handover rate, namely the number of successful handovers per minute, •• average delivered data per handover, namely the total delivered data over the total number of handover, and • • • handover delay ratio, namely the ratio between the time required for performing the handover and total connection time.

In practice, we used an array of commercial low-power LEDs as APs, in order to build a small-scale setup. Each optical transmitter is connected to a dedicated output port of an Arduino 1 in order to control and drive separately each LED. A simple receiver consisting of a low-cost PD and other passive elements is used for delivering the data to the signal process unity, mainly composed of a USRP 2920 and a Low-Frequency daughterboard. The distance between the ceiling of the APs setup and the plane of the mobile receiver is constant, while the number of LEDs and the distance between them is properly modified to allow performance evaluation for different linear node densities. As a benchmark, we model the SNR-based handover mechanism with the same parameters, and we compared both mechanisms in simulation and experimental tests. In the SNR-based case, the handover decision is based on the maximum received power and the connection time, while, for the sake of fairness, we applied the ADM on top of both handover mechanisms. Table 4.4 shows the main system parameters used in the simulation and experimental tests.

Assuming the testbed scenarios of Figure 4.7, different configurations of LEDs represent different nodes' linear densities while feeding the signal to the USRP at different time intervals manipulates different speeds. As the mobile node moves along the coverage area of a given AP, the SNR metric is used to measure the link QoS and allocate the modulation scheme for the next transmission bursts, whereas the interference is mitigated based on the frequency shift keying. When the error probability increases as a result of the degradation of the link quality, the INR-based handover nominates an alternative AP with the highest connection time. On the other hand, the SNR-based algorithm is suggesting the link with the highest received power that lasts at least 𝑇 𝑐 seconds, otherwise it backs off the scanning for 𝑡 𝑠 seconds.

In Figure 4 In Figure 4.9, we assess the impact of the node density on the average delivered data per handover at speed 0.3 𝑚𝑝𝑠 and 0.15 𝑚𝑝𝑠. In both medium access schemes, the transmission is carried out when the frontend device is well covered by the AP (i.e., 𝑆𝑁 𝑅 ≥ 𝛼). Giving 𝑡 𝑠 the available time for transmission, at rapid gait (i.e., 0.3 𝑚𝑝𝑠) the connection time is shorter than the one of lower speed (i.e., 0.15 𝑚𝑝𝑠) providing bigger portion of time for transmissions in different bitrate according to Table 4.3. As a result, the average delivered data is larger for the higher speed than the lower one. It is also obvious from Figure 4.9 that the INR-based mechanism always transmits more data per access point than the SNR-based scenario, that is not because of higher data rate obtained with our proposed scheme (i.e., the transmission scheme is the same at both proposed scheme and the benchmark), but because the INR-based mechanism makes much less handovers for the same AP distribution.

As the 𝜌 𝑙 increases the average delivered data decreases in both schemes with a slight incline for the INR-based scheme.

The evolution of the handover delay ratio compared to AP density for different velocities is depicted in Figure 4.10 based on the delay ratio model explained in section 4.3. At higher velocities, the connection time is lower resulting in a less efficient handover delay ratio. For a given velocity, at the low-density scenarios the SNR-based performs better due to the shorter handover frame size. As the node density increases, the number of SNR-based handovers grows linearly. Simultaneously, the dense AP deployment boosts the received power at the front-end device which in return applies higher modulation levels and increases the bitrate, although the handover rate progresses faster than the bitrate, That is why the SNR-based handover delay ratio is monotonically increasing. On the other side, the interference-based handover mechanism substantially outperforms the SNR-based handover by recovering the higher overhead with the lower 𝐻𝑂 𝑟𝑎𝑡𝑒 . The ratio 𝐻𝑂 𝑟 𝑎𝑡𝑒 𝑅 𝑏 in INR-based scheme is less than unity because the 𝐻𝑂 𝑟𝑎𝑡𝑒 reaches the saturation level at the high density, while the 𝑅 𝑏 continues increasing leading to decreasing delay ratio.

Conclusion

An Area Update (TAU) and Paging messages, which are essential to exchange UE-specific information with the network. To achieve cost-efficient resource provisioning, many solutions have been proposed for TAU and Paging management to optimize not only UE experience (i.e., battery power consumption) but also network resources (i.e., bandwidth). [START_REF] Alsaeedy | A review of mobility management entity in LTE networks: Power consumption and signaling overhead[END_REF].

On the other hand, vehicular VLC has less overhead in terms of channel access regulation and signaling, owing to short-range and point-topoint link style [START_REF] Aldalbahi | Extending ns3 to simulate visible light communication at network-level[END_REF]. Therefore, vehicular traffic may be handled jointly through these two technologies. This chapter compares LTE and VLC performances in vehicular communication. A new power model has been suggested to measure energy efficiency at the transmitter and the receiver, in addition to the packet reception ratio, and latency metrics.

The two technologies are united through a vertical handover mechanism called CV2LC. Vertical handover guarantees a seamless transition from one technology to another.

C-V2X

C of parameters such as the number of sub-channels and the number of RBs per sub-channels. These parameters are configurable by users or operators when vehicles are covered by the cellular network. In LTE-V2X Mode 4, vehicles use the sensing-based Semi-Persistent Scheduling (SPS) defined in ITS Release 14 to autonomously sense, identify and select the unoccupied sub-channels. For this aim, SPS transmits Resource Reservation Interval (RRI) within SCI to inform the neighboring vehicles when they will utilize the reserved sub-channels for their next transmission [START_REF] Molina-Masegosa | Comparison of IEEE 802.11p and LTE-V2X: An Evaluation With Periodic and Aperiodic Messages of Constant and Variable Size[END_REF][START_REF]LTE; Evolved Universal Terrestrial Radio Access (E-UTRA); Physical layer procedure[END_REF]. A vehicle that uses a given sub-channel to transmit its current TB (and its associated SCI) at time 𝑡 will use the RRI to notify nearby vehicles that it plans to use the same sub-channel for its next transmission at t+RRI. The RRI is then used to prevent other vehicles from utilizing the same sub-channel(s). The RRI can be configured equal to 20 ms, 50 ms, 100 ms, or any multiple of 100 ms. The 3GPP standard does not fix a value of the RRI and its configuration is up to UE implementation. The configuration of the RRI has an important impact on the operation of the sensing-based SPS scheme. Its value should be adapted as much as possible to the characteristics of the messages that vehicles must transmit. Vehicles use the selected sub-channel(s) for a number of consecutive Reselection Counter transmissions. The reselection counter is randomly selected between 5 and 15 for RRI = 100 ms (or any multiple of 100 ms). The reselection Counter is decremented by 1 after each transmission, and a new value must be selected every time a vehicle needs to reserve new sub-channel(s). New sub-channel(s) must be reserved if at least one of the following conditions is satisfied:

▶ New sub-channel(s) must be reserved with probability(1 -𝑃) if the Reselection Counter reaches 0. P can be configured between 0 and 0.8. Increasing P augments the probability to maintain selected sub-channel(s) for longer periods of time. This provides a more stable sensing environment. However, increasing P also augments the probability of persistent packet collisions between two vehicles that select the same sub-channel(s). If a vehicle does not maintain the current reservation when Reselection Counter reaches 0, it notifies other nodes by setting the RRI in the SCI equal to 0.

▶ New sub-channel(s) must be reserved if the new packet or TB does not fit in the reserved sub-channel(s).

▶ New sub-channel(s) must be reserved if the current reservation cannot satisfy the latency deadline of a new packet. This happens if the time until the next reserved sub-channel(s) is higher than the latency deadline of the new packet.

The process to select and reserve new sub-channel(s) is referred to as re-selections. To select new sub-channel(s) at time T, the ego vehicle executes the following three steps of the sensing-based SPS scheme:

▶ Step 1.
The ego vehicle identifies first the Candidate Single Subframe Resources (CSR) within the Selection Window. The Selection Window (Figure 5.1) is the time period between T and the latency deadline of the incoming packet (equal or lower than 100 ms). A CSR is a group of adjacent sub-channels within the same sub-frame where the new SCI+TB to be transmitted fits.

▶

Step 2. The ego vehicle excludes the identified CSRs that it estimates will be used by other vehicles. To this aim, the ego vehicle senses the transmissions from other vehicles during the so-called Sensing

Window. The Sensing Window is the time period that includes the last 1000 sub-frames before T (Figure 5.1). A CSR is excluded if the two following conditions are met:

1. the ego vehicle has received an SCI from another vehicle indicating that it will utilize this CSR in the current Selection Window or at the same time as the ego vehicle will need it to transmit any of its following Reselection Counter transmissions 2. the ego vehicle excludes a CSR if its average Reference Signal Received Power (RSRP) measured over the TB associated to the corresponding SCI is higher than a given threshold. The RSRP threshold is a configurable parameter.

The ego vehicle builds a list L1 with all the CSRs that have not been excluded. L 1 must include at least 20% of all CSRs in the Selection Window. Otherwise, Step 2 is iteratively executed increasing the RSRP threshold by 3 dB at each iteration until the 20% target is met.

▶ Step 3. The ego vehicle builds a list L2 with the CSRs included in L1 that has the lowest average Received Signal Strength Indicator (RSSI) over all its RBs. This RSSI value is averaged over all the previous 𝑇 𝐶𝑆𝑅 -𝑇 𝐼𝑃𝐼 • 𝑗 sub-frames where 𝑇 𝐼𝑃𝐼 = 100 ms. The total number of CSRs in L2 must be equal to 20% of all CSRs in the Selection Window. The ego vehicle randomly selects a CSR from L2 to transmit its new packet, and it maintains the selection for its next Reselection Counter transmissions.

Semi-persistent scheduling has severe impacts on LTE-V2X performance. The sensing window increase, and obliged the receiver to detect the signaling for a longer time, which in consequence increases the power consumption for signaling messages. Moreover, the re-selection period increases the Packet Inter-Reception (PIR). PIR is the time between two successful receptions of regularly transmitted messages [START_REF] Eckermann | Performance analysis of C-V2X mode 4 communication introducing an open-source C-V2X simulator[END_REF].

LTE Power Consumption

The energy efficiency of communication networks is progressively attracting the research communities due to the exploding wireless technologies. The energy efficiency is usually evaluated in an extensive measurements regime using small-scale or actual devices which increases the total cost of projects and requires further expertise for implementation. In addition, new energy-saving methods and optimization techniques proposed in academia, require a comprehensive power model considering all the major energy-consuming components and their performance during different phases of transmission, reception, and ideal states. Nokia proposed a power model which considers only radio resource configuration mode for 3GPP but it does not take into account different data rate power control at the transmitter [START_REF] Jensen | LTE UE Power Consumption Model: For System Level Energy and Performance Optimization[END_REF]. The chip manufacturers have detailed models based on their development platforms, however, they are confidential.

Launching LTE opened new horizons to empirical models. A precise model based on the LTE USB dongle has been proposed in [START_REF] Jensen | LTE UE Power Consumption Model: For System Level Energy and Performance Optimization[END_REF] which is robust and transferable. This model describes an LTE user equipment (UE) radio modem which is depending on power levels and data rates. Transmitter DSP In the LTE transmitter, the main task of digital signal processing is to turbo-encode user data with Forward Error Correction codes. Turbo encoding relies on convolutional encoding and generates a bit stream with a given code rate. The Turbo encoding complexity scales linearly with the amount of data to encode which is set by the Transport Block Size (TBS) e.g., the UL data rate, but is independent of the UL Tx power [START_REF] Gpp | Multiplexing and channel coding[END_REF].

DAC & ADC Digital to analog converter, converts the digitally processed signals to the analog waveform at the transmitter. On the other hand, the analog waveform at the receiver is digitized by the analog-to-digital converter.

Transmitter ASP Generally, the analog signal processing at the transmitter (ASP Tx) will not depend on the uplink (UL) data rate, but when the modulation format is changed, the Peak-to-Average Power Ratio (PAPR) is affected. This involves the Power Amplifier (PA), and adjusts its performance to comply with the transmission emission requirements in [START_REF] Gpp | UE radio transmission and reception[END_REF], such as the Adjacent Channel Leakage Ratio (ACLR), and this may affect the power consumption. The ASP Tx will obviously depend on the UL Tx power. A single PA only has one output power level where it achieves its maximum energy efficiency, and therefore researchers develop methods to increase the efficiency at other output power levels. These include the use of multiple PAs [START_REF] Ghiotto | Dual-Mode Power Amplifier Module with In-Band Reconfigurable Output Power for Multifunctional Radar and Radio Communication Systems[END_REF], supply voltage and bias switching, and the envelope tracking concept [START_REF] Li | A SiGe envelope-tracking power amplifier with an integrated CMOS envelope modulator for Mobile WiMAX/3GPP LTE transmitters[END_REF].

Receiver ASP The receiver analog signal processing power consumption is expected to be independent of the downlink (DL) data rate, but it will depend on the DL Rx power level. The reason is that the RF contains gain controls and low noise amplifiers, which are used to obtain a certain signal level at the ADC. If the DL received power level is high, the gain in the aforementioned circuits can be reduced, and they may be powered off in order to reduce power consumption.

Receiver DSP The majority of the complexity at the receiver digital signal processing, e.g., channel estimation and equalization, is independent of the DL data rate. To decode the received user data, the UE applies turbo decoding, which is an iterative algorithm and the most complex computational task in the digital baseband. To support the high data rates of LTE, a parallel turbo decoder architecture is required. The complexity and thus the power consumption scales linearly with the DL data rate [START_REF] Anghel | LTE Turbo Decoding Parallel Architecture with Single Interleaver Implemented on FPGA[END_REF].

UE LTE Power Model

Based on the review of the six physical components of the LTE UE device, the model is defined as 5.1:

𝑃 𝑇𝑜𝑡𝑎𝑙 = 𝑃 𝑇𝑥 + 𝑃 𝑅𝑥 (5.1)
where 𝑃 𝑇𝑜𝑡𝑎𝑙 is the total power consumption. The 𝑃 𝑇𝑥 is the transmitter power consumption derived from 5.2 and 𝑃 𝑅𝑥 is the receiver one computed as 5.3.

𝑃 𝑇𝑥 = 𝑃 𝐷𝑆𝑃,𝑇𝑥 + 𝑃 𝐴𝑆𝑃,𝑇𝑥 + 𝑃 𝐷𝐴𝐶 (5.2)
𝑃 𝑇𝑥 = 𝑃 𝐷𝑆𝑃,𝑅𝑥 + 𝑃 𝐴𝑆𝑃,𝑅𝑥 + 𝑃 𝐴𝐷𝐶 (5.3)
The ADC and DAC power consumption is represented by the offset 𝑏 and the slope 𝑘 of the ADC/DAC circuit design which is further scaled with the operating bandwidth B.

𝑃 𝐷𝐴𝐶/𝐴𝐷𝐶 = 𝐵 • 𝑘 𝐷𝐴𝐶/𝐴𝐷𝐶 + 𝑏 𝐷𝐴𝐶/𝐴𝐷𝐶 (5.4)
The digital signal processing unit power consumption is defined as 5.5 and it is assumed identical for the transmitter and the receiver [START_REF] Desset | Flexible power modeling of LTE base stations[END_REF].

𝑃 𝐷𝑆𝑃 = 𝑃 𝑙𝑒 𝑎𝑘 • 𝑃 𝑑𝑦𝑛𝑎𝑚𝑖𝑐 (5.5)
where 𝑃 𝑑𝑦𝑛𝑎𝑚𝑖𝑐 represents the power dissipation at the dynamic charging and discharging of the Complementary Metal Oxide Semiconductors (CMOS) inherent capacitors, and 𝑃 𝑙𝑒 𝑎𝑘 denotes the leakage power dissipated due to reverse leakage of the employed CMOS switches.

𝑃 𝑙𝑒 𝑎𝑘 = 𝜂 𝑙𝑒 𝑎𝑘 • 𝑃 𝑑𝑦𝑛𝑎𝑚𝑖𝑐,𝑟𝑒 𝑓 (5.6)
where 𝜂 𝑙𝑒 𝑎𝑘 stands for the leakage power ratio which is measured in Giga operations per second per watt (GOPS/W), and 𝑃 𝑑𝑦𝑛𝑎𝑚𝑖𝑐,𝑟𝑒 𝑓 refers to the dynamic power at the reference bandwidth 𝐵 𝑟𝑒 𝑓 [𝐻𝑧]

𝑃 𝑑𝑦𝑛𝑎𝑚𝑖𝑐 = 𝑂 𝐶 • 𝐵 𝜂 𝐶𝑀𝑂𝑆 • 𝐵 𝑟𝑒 𝑓 (5.7)
The 𝑂 𝐶 represents the digital computational complexity function at the reference bandwidth 𝐵 𝑟𝑒 𝑓 which is scaled linearly with the operating bandwidth value (𝐵). 𝜂 𝐶𝑀𝑂𝑆 is the intrinsic CMOS power-efficiency factor.

The analog unit includes different elements of a transmitter and the receiver such as carrier generation, modulator, mixer, low noise amplifier (LNA), variable gain amplifier (VGA), filter, buffer, and Power Amplifier (PA). Direct conversion transceiver is a popular architecture for LTE-UE (see Figure 5.3) [START_REF] Abidi | Direct-conversion radio transceivers for digital communications[END_REF]. Direct conversion means that an RF signal is directly down-converted to a Base-band (BB) signal or vice versa without any Intermediate Frequency (IF) stages, and therefore it is also referred to as zero IF architecture. The direct conversion architecture has many attractive features. The direct-conversion receiver has no IF, and thus the expensive IF passive filter (SAW filter) can be eliminated, and then the cost and size of the overall transceiver are reduced. The channel filtering of the direct-conversion receiver is implemented in the analog baseband by means of an active low-pass filter. In a direct conversion receiver, the function of the duplexer band pass filter (BPF) is to suppress the leakage power of the transmission and other out-of-receiver band interference.

The received signal after pre-selecting the duplexer is amplified by an LNA, and it is further filtered by an RF filter. The filtered RF signal is then directly down-converted into In-phase and Quadrature baseband (BB) signals by an I/Q down converter which is also called a quadrature demodulator. The BB signals in the I and Q channels are synchronously amplified, but their 90 • phase offset will be kept unchanged as possible.

In the direct conversion receiver, the overall receiver gain is obtained from the analog baseband block when the receiver operates at its high gain mode. There exists a low pass channel filter in each of the I and Q channels. Unlike the superheterodyne receiver, channel selectivity mainly depends on the stop-band rejection of the low-pass filter without any passive band-pass filter assistance. where 𝑃 𝐿𝑁 𝐴 stands for low-noise amplifier power consumption, 𝑃 𝑎𝑡𝑡𝑒𝑛𝑢𝑎𝑡𝑜𝑟 is the power lost in the main variable attenuator, and 𝑃 𝑚𝑖𝑥𝑒𝑟 is the dual mixer power.

VLC Power Consumption

A similar power consumption model is presented based on the VLC system block diagram of Figure 5.4, where the front-end blocks are divided into digital and analog components according to the place of DAC and ADC converters in the transmitter and the receiver sides respectively [START_REF] Kong | Power Consumption Evaluation in High Speed Visible Light Communication Systems[END_REF]. This model accounts for the most significant power consumer VLC components, specifically:

▶ At the transmitter side the signals are processed digitally using Digital Signal Processing and then converted to an analog waveform by digital to analog converter DAC.

▶ Transmitter Amplifier amplifies and biases the analog signal to fit the linear region of LED transfer characteristic.

▶ LED transforms the electrical signal to visible light and then passed it to the optical wireless channel.

▶ At the receiver side, the PD is used as a passive element to convert the optical signal back to a current signal. When a bias is applied to the photodiode, the current output can be controlled to provide thresholding, linear response, or nonlinear response.

▶ The trans-impedance amplifier TIA alters the current to a voltage signal.

▶ The analog voltage waveform is digitized by the analog to digital converter ADC and eventually delivered to DSP for further processing.

Analogue power consumption:

The analog power consumption at the transmitter part of this model can be decomposed to the power consumption at the transmitter amplifier and the power consumption of the LEDs, as 5.10:

𝑃 𝐴𝑆𝑃,𝑇𝑥 = 𝑃 𝑇𝑥 𝐴𝑚𝑝. + 𝑛 • 𝑃 𝐿𝐸𝐷 (5.10) The LED's power consumption (i.e., 𝑃 𝐿𝐸𝐷 is determined by the DC bias level and the total number of the deployed LEDs (i.e., 𝑛). In the same way, the analog power consumption at the receiver part is decomposed to the PD power consumption and the trans-impedance amplifier power consumption, as 5.11:

𝑃 𝐴𝑆𝑃,𝑅𝑥 = 𝑚 • 𝑃 𝑃𝐷 + 𝑃 𝑇𝐼𝐴 (5.11)
where 𝑚 is the number of photodiodes and bounded trans-impedance amplifiers.

Digital power consumption: Due to the similarity in the digital processing techniques between RF and VLC, the same power consumption model is adopted in this study [START_REF] Kong | Power Consumption Evaluation in High Speed Visible Light Communication Systems[END_REF][START_REF] Holtkamp | A Parameterized Base Station Power Model[END_REF].

Energy Efficiency

To model the energy consumption during one transmission time interval (TTI), one can relay on the conversion of the power to energy in different states as 5.12, 5.13 and 5.14: (5.17)

𝐸 𝑇𝑇𝐼 = 𝐸 𝑇𝑥 +
The equivalent power-related version of 5.17 is derived as 5.18

𝐸𝐸 = 𝑍/𝐷 𝑘 1 + 𝑘 2 𝑃 𝑡 /𝑅 𝑏 (5.18)
𝑘 1 , 𝑘 2 coefficients that depend on the technology. ▶ The absolute difference between the current velocity and the velocity included in the previous CAM exceeds 0.5 m/s.

▶ The absolute difference between the current heading of the vehicle and the heading included in its previous CAM exceeds 4 • .

▶ The time elapsed since the last CAM was generated is equal to or higher than 1 s.

These generation rules are applicable regardless of the access technology.

Most of the basic awareness traffic in C-V2X is encapsulated either in broadcast cooperative awareness message (CAM) specified by the European Telecommunications Standards Institute (ETSI), or in Broadcast Basic Safety Message (BSM) specified by the Society of Automotive Engineers (SAE). These messages contain basic information about the position, speed, or direction of the transmitting vehicle. In LTE-V2I, CAMs are generated and broadcasted by the vehicle through a given wireless interface (ITS-G5) while the V2V communication employs PC5 or sidelink to share CAMs among cars [START_REF] Santa | Experimental evaluation of CAM and DENM messaging services in vehicular communications[END_REF]. The on-board C-V2X units -a small scale base station (Femto) used in cars-use more power-efficient dedicated components compared to large base stations (macro and micro), the downscaling factor defined in [START_REF] Desset | Flexible power modeling of LTE base stations[END_REF] is used to reduce the power on smaller base station due to less constraining space and different hardware implementation. The reason is twofold: • The amount of blockers, a small base station has to face is smaller, leading to more relaxed linearity specs, and hence less power is needed. Femtocells are the smallest unit in the LTE system hierarchy which suits the C-V2X ranges (10-1000m) [START_REF] Chekkouri | 10 -Connected vehicles in an intelligent transport system[END_REF]. The downscale factor for LTEfemtocell is 12. The power amplifier behavior can not be captured by a single reference power number and scaling rules. Hence, the PA model is represented by a table containing measurements of output power versus consumed power. Measured points differ in requested output power and in the tuning of the 1 dB compression point. The power model picks up the point with minimal power consumption that is satisfying the output power and linearity constraints. The maximum total output power for femtocells is 20 dBm, and its minimum power consumption is 650 mW. Table 5.1 represents the power consumption of the analogue components in LTE on-board unit. In order to simulate the MAC performance of the LTE-V2X the following scenario is assumed: n eNBs are uniformly distributed such that the Tx-Rx distance will meet the LTE rel.14 requirements in terms of Packet Reception Ratio(PRR) equal to 95%. In fact, in order to concentrate on the MAC performance we cancel the performance degradation of the physical layer (propagation loss and shadowing effect) [START_REF] Molina-Masegosa | Configuration of the C-V2X mode 4 sidelink PC5 interface for vehicular communication[END_REF] following the WINNER+B1 channel model by the 3GPP [START_REF] Gpp | Study on LTE-based V2X services[END_REF]. The B1 channel model for the 5.9 GHz band is calculated as follows:

• LOS for 30 𝑚 < 𝑑 < 𝑑 ′ 𝐵𝑃 is calculated by:

𝑑 ′ 𝐵𝑃 = 4 • ℎ ′ 𝐵𝑆 • ℎ ′ 𝑀𝑆 • 𝑓 𝑐 /𝑐 (5.23)
where the effective antenna height ℎ ′ 𝐵𝑆 = ℎ 𝐵𝑆 -1 𝑚 and ℎ ′ 𝑀𝑆 = ℎ 𝑀𝑆 -1 𝑚 and 𝑐 = 3 • 10 8 𝑚/𝑠 [START_REF] Eckermann | Performance analysis of C-V2X mode 4 communication introducing an open-source C-V2X simulator[END_REF] Based on [START_REF] Gpp | Study on LTE-based V2X services[END_REF] the antenna height is set to ℎ 𝐵𝑆 = ℎ 𝑀𝑆 = 1.5 𝑚 for V2V communications and ℎ 𝐵𝑆 = 5 𝑚 , ℎ 𝑀𝑆 = 1. [START_REF]Lighting Design Guidance[END_REF]. In this design, the pole height is 8-10 m and the spacing between two light poles should be roughly 2.5-3 times the height of the pole. This regulation let us to uniformly distribute the light poles with 25-meter spacing in highway scenarios and 23 meters in urban scenarios. The vehicle velocity is defined according to the federal highway administration of US government since the urban scenario follows the Manhattan mobility scenarios. Following this regulation, the speed in the urban areas is changed between 45 to 72 and on highways is set between 90 and 105 kilometers per hour [START_REF]Speed Limits[END_REF].

OOk single carrier modulation has been used for its low complexity and robustness. The computational complexity factor 𝑂 𝐶 for OOK modulation is set to 505.15 GOPS at 20 MHz reference bandwidth 𝐵 𝑟𝑒 𝑓 .

According to [START_REF] Kong | Power Consumption Evaluation in High Speed Visible Light Communication Systems[END_REF], CMOS power efficiency is 3.6𝑒 + 4 GOPS/W, while the leakage ratio was 24. . In figure 5.8 the receiver energy efficiency for the SNR-based handover mechanism has been presented under continuous transmission/reception. In the V2I scenarios, receiver energy efficiency is steady because the data traffic flow and the power consumption do not change with increasing the traffic density. The data traffic flow is constant because the transmission period (equal to simulation time), as well as the number of received packets, is stable. Moreover, the receiver energy efficiency increase in the V2V scenario according to figure 5.8a. In V2V cases the CAM dissemination rate increased as a consequence of more received packets when the traffic density increased. As a result, the receiver receives more and more data per unit of energy. In figure 5.8b, the same metric has been examined for INR-based regular transmission. The receiver efficiency in energy consumption is similar to the SNR-based performance using the same transmission method and in both cases, the receiver can not receives more than 2.1-kilobits per joule. The performance of the adaptive transmission in terms of receiver energy efficiency is higher than the regular transmission for SNR-based and INR-based handover mechanisms according to figures 5.8c and 5.8d. The difference is that in the V2V scenarios the reception period (i.e., 𝑇) is lower in a low traffic density and it increased to be equal regular transmission period in high traffic density. Finally, the INR-based adaptive transmission is outperforming the other 3 schemes in receiver energy efficiency by means of restricting the working time of the most energy-consuming components to the connection interval.

In figure 5.9 the LTE-V2X receiver energy efficiency in respect of traffic density is presented. Compared to the VLC technology, the LTE receiver, collect more information per unit of energy (e.g., 𝐽𝑜𝑢𝑙𝑒). In vehicular to vehicular scenarios, the performance is slightly enhanced in dense scenarios because the receiver is receiving more and more bits per unit As a matter of fact, the signaling overhead in a vibrant scenario like a highway prevents the SNR-based mechanism from transmitting the CAM messages despite being exposed to a potential VLC infrastructure all the time. The V2V communication energy efficiency is degrading by increasing the traffic density. In SNR-based for example, as the number of surrounding nodes is increased, the signaling overhead increases and as a result, the amount of energy that should be spent to disseminate the CAM massage is spent for signaling. Conversely, in the INR-based algorithm, the 𝐸𝐸 𝑇𝑥 performance is improving with traffic density augmentation owing to the lower number of handovers and overhead in general. The black dash-line shows the transmitter's energy efficiency when it follows the regular transmission method. It is obvious that the energy consumption in this method is not efficient and it represents the baseline for any energy optimization technique. The energy efficiency is less reliant on the traffic density in the LTE-V2X transmitter. The LTE-V2X transmitters are very harsh in energy consumption such that they can not transmit more than a few kilo bites per Joule of energy. Figure 5.11 shows the LTE transmitter energy efficiency in different scenarios. The best C-V2X can do in terms of transmitter energy efficiency is at highway V2I scenario.

Packet reception ratio (PRR) is defined as the number of correctly received packets to the total transmitted packets and represented through (5.24).

𝑃𝑅𝑅 = 𝑅𝑒 𝑐𝑒 𝑖𝑣𝑒 𝑑 𝑃𝑎𝑐 𝑘𝑒𝑡𝑠 𝑇𝑟 𝑎𝑛𝑠𝑚𝑖𝑡𝑡𝑒 𝑑 𝑃𝑎𝑐 𝑘𝑒𝑡𝑠 (5.24)
Packet accounts are delivered if the number of erroneous bits (symbol) is less than the coding threshold. Since we do not use any channel coding scheme (FEC, ARQ, etc), a packet is correctly received when all the packet's bits(symbols) are correctly detected. Assuming OOK modulation scheme [START_REF] Aldalbahi | Visible Light Communication Module: An Open Source Extension to the ns3 Network Simulator With Real System Validation[END_REF] has been used then the Packet Error Ratio is defined as 5.25:

𝑃𝐸𝑅 = 1 -(1 -𝐵𝐸𝑅) 𝑚 (5.25)
Where m is the packet size in bits and BER is the bit error rate for the OOK modulation scheme defined as 5.26 [START_REF] Rahaim | Optical interference analysis in Visible Light Communication networks[END_REF]:

𝐵𝐸𝑅 𝑂𝑂𝐾 = 0.5 𝑄(𝑆𝑁 𝑅 𝑜 ) (5.26) in 5.26 𝑄 is the tail probability of the standard normal distribution and 𝑆𝑁 𝑅 𝑜 is the optical signal to noise ratio defined as 3.13

In figure 5.12a the PRR of SNR-based with the regular transmission is gradually improved for all scenarios but with a different slope, as the urban and highway V2V is highly dependent on the traffic density such that, the higher traffic density decreases the distance among vehicles and so increase the received power of the VLC signal. In that case, the SNR is increased and the packets are more likely received successfully. On the other hand, in the vehicular to infrastructure (V2I) VLC, the density of the infrastructures (street light poles) is constant and they are arranged in a way to provide sufficient illumination as a primary purpose along the streets and the roads based on street lighting standards [START_REF]Lighting design guidance Global Designing Cities Initiative[END_REF] and the VLC connectivity as a secondary purpose. The PRR for V2I scenarios remains almost constant when the number of mobile devices increases, since the distribution of the infrastructure does not change and as a result, the covered area of the infrastructure is constant. According to [START_REF]Lighting design guidance Global Designing Cities Initiative[END_REF], spacing among highway lighting infrastructures is higher than urban infrastructures which explains why the urban V2I PRR curve is upper than highway V2I 5.12a. Figure 5.12b pictures the INR-based packet reception ratio when the transmission is regular. The PRR has been enhanced a little bit for all scenarios because the INR-based handover mechanism is designed to connect the most durable access point and so reducing the possibility of disconnection. Similarly, the vehicular-tovehicular packet delivery ratio is much more responsive to the traffic density increment compared to the vehicular-to-infrastructure one. In the adaptive transmission case (figures 5.12a and 5.12b) the performance is nearly comparable with a slight preference in INR-based regular transmission V2I cases. For adaptive transmission schemes, the PRR is much higher than the regular transmission schemes because in adaptive transmission schemes the transmitter actually transmits only when the link quality indicator (SNR in SNR-based and INR in INR-based) is above the threshold which gives a higher probability of successful transmission. More precisely, the augmentation in the PRR metric of adaptive transmission is due to the reduction of uncertain transmission. In the next world, the packet reception ratio of V2V is smaller, due to the lower coverage range of onboard modules in the vehicles compared to the eNB station at V2I scenarios. PRR is decreased by increasing the number of vehicles in V2V urban and highway scenarios. In cellular V2V, each vehicle has to manage its own communication session in a distributed way, it gives higher chance to an individual mobile node to find a free channel for transmission at lower density while in the higher traffic density the completion to acquire RF resource for transmission is stronger and decrease the chance of finding a free channel, so the PRR decreases.

Vehicular applications have some requirements in terms of latency. In [START_REF] Cen | Enabling Vehicular Visible Light Communication (V2LC) Networks[END_REF] latency has been defined as the maximum time span during which vehicular traffic may be successfully delivered to the target vehicle. In our application, latency is the time delay from the CAM generated, until the successful delivery to the destination. In Figure 5.14 the latency of LTE-V2X and VLC is compared in multiple scenarios. Generally, the latency in LTE-V2X is much longer than the end-to-end latency in VLC. In LTE-V2V scenarios, increasing the traffic density decreases the distance among communicating vehicles which reduces the latency by its part. However, the latency in V2I scenarios does not change significantly in dense traffic in both technologies, since the average distance between the cars and the infrastructure is constant. This distance is much lower in VLC technology (the coverage range of VLC technology is lower than LTE-V2X) which makes communication faster.

CV2LC

In this section, a new vertical handover mechanism called Cellular Vehicular Visible Light Communication (CV2LC) has been proposed. Owing to the multiple advantages that have been discussed in the earlier section, CV2LC prefers VLC technologies for CAM dissemination. VLC works as a complement to cellular LTE-V2X technology, but in this model VLC is the primary transmission option and LTE radio technology is the second option for data transmission. The main trigger for vertical handover is reliability. Such that when the PER degrades below the threshold, CV2LC switches to LTE to maintain an acceptable packet reception ratio (PRR). Moreover, the energy consumption and the delay performance of these handover mechanisms give a good compromise between ad hoc VLC and LTE. When the mobile node does not have any active ink, the CAM generation is prevented. A heterogeneous LTE-VLC network has been simulated at vehicular applications for V2V and V2I communications in urban and highway scenarios. The CV2LC performance is evaluated in terms of PRR, latency, transmitter EE, and receiver EE.

Simulation Results

The packet reception ratio is presented in figure 5.16 in respect of the traffic density, and it is visible that the 95% 3GPP baseline is always respected because the reliability (represented in PER) is the triggering metric for CV2LC protocol. When the PER degrades below the given threshold (10e-3), the mobile node use INR-based to select an alternative VLC link to send CAM and if it fails, the LTE is the last option. PRR is slightly increasing in V2V communication when the traffic increases, however PRR in vehicular to infrastructure is almost constant. The CV2LC performance in V2I is higher than V2V and Highway V2I has the best PRR. Due to the fact that VLC does not fulfill the 3GPP requirement in terms of PRR, in the highway V2I, CV2LC totally relies on C-V2X for CAM transmission.

The energy efficiency at the receiver at CV2LC has been improved compared to the ad hoc V2LC especially in high traffic density according to figure 5.17. In this figure, when the traffic density is growing, it has a positive effect on the V2V receiver EE, while it is less effective in V2I scenarios. Moreover, the receiver in urban V2V has the highest performance, and the lowest performance is happen in the urban V2V environment. The receiver energy efficiency in highway V2I is equivalent to the C-V2I curve at the same condition. It means, the CV2LC is mostly using LTE in highway V2I.

Figure 5.18 shows the energy efficiency at the transmitter part in relation to the traffic density. Compared to the C-V2X, the transmitter energy efficiency is improved in urban V2I, urban V2V, and highway V2V, and it is identical to C-V2I in highways. In the sparse traffic density, the CV2LC uses the energy more efficiently at the transmitter to send CAMs to other mobile nodes, and as the traffic density increases, the transmitter energy efficiency decreases. In V2I communication, the energy efficiency at the transmitter is steady but it is higher than ad hoc C-V2X and V2LC.

The latency of CV2LC has been shown in figure 5.19 when the traffic density grows in different scenarios. The CV2LC latency is improved by one order of magnitude compared to ad hoc C-V2X in vehicularto-vehicular communication. In the urban V2I scenario, the latency is decreased significantly, while in highway V2I, CV2LC and CV2X are identical. At first look at figure 5.20d, it is understandable that the energy efficiency at the transmitter is lower than the receiver, especially in C-V2X. Moreover, the VLC technology is more efficient than LTE in all scenarios apart from highway V2I. Accordingly, the CV2LC algorithm is more stable in energy consumption in the transition from low density to high density.

Conclusion

This chapter was dedicated to the vertical handover mechanism. In our case, The VLC has been chosen as a primary technology to transmit cooperative awareness messages in vehicular scenarios. In addition to VLC, LTE is supporting CAM dissemination when VLC is unavailable. Vertical handover is a frequent technique to keep a mobile node connected by switching a connection link from one technology to another. The selection of using VLC rather than LTE was motivated by packet reception ratio, latency, and energy consumption. A new theoretical power model has been suggested in this chapter to analyze the energy efficiency of the transmitter and the receiver. Finally, the CV2LC handover algorithm was implemented in the ns-3 simulator with supplementary performance assessment tools. The current study aimed to establish a stable VLC link between mobile nodes. The main challenges in maintaining a good QoS in the vehicular visible light network was mobility management and line of sight. We proposed different techniques to deal with these challenges. A realistic channel model based on the outdoor environment was presented and implemented in the ns3 simulator. Two different handover mechanisms and adaptive modulation schemes have been proposed to prolong the connection time of V2LC networks. The findings of this study have been verified through mathematical models, simulations, and experimentation.

Conclusions and

Conclusions

Chapter 1 represented a summary of the thesis contents, including the definition of VLC and vehicular communication technologies, challenges, contributions, and the supplementary activities during the 3 years of Ph.D. In Chapter 2, a short history of VLC is presented. In addition to a detailed explanation of different technologies used in vehicular communications. The up-to-date state of the art was listed in this chapter according to the perspective of this thesis. Chapter 3 included the first bunch of contributions to this thesis. First of all, we defined a channel model for outdoor VLC including Lambertian emission and climate distortion models. For the more, link adaptive protocol has been suggested to scan the available VLC links and get associated to, for higher spectrum efficiency, upgrades the modulation level according to the link quality. This algorithm was performed in the ns3-V2LC networks module which includes a realistic channel model, sumo mobility, and LAP protocol. We assessed the performance of the V2LC network via multiple metrics in comparison with slotted-aloha, including outage probability, and goodput. Finally, we did an interesting analysis of the relation between pilot rate and protocol efficiency. Interference based haNdover mechanism for VISIBle Light nEtworks (INVISIBLE) was proposed in Chapter 4. It utilizes INR and IIR metrics instead of a conventional signalbased metric to assess the link quality. According to our study, normal Gaussian distribution is not a precise model in dominant interference systems. Therefore, INR defined the system dominant disturbances and IIR nominate the dominant interferer to proceed with the channel access procedure. When the dominant interferer verified, the distribution closely matches the distribution of the dominant interferer, while in noise dominant system the distribution is assumed Gaussian. Following INVISIBLE in presence of multiple interferer, the QoS requirement forces to pick the candidate access point which has the longest connection time. This model has been validated in ns3 simulator as well as a softwaredefined approach. The practical part in a small scale was composed of low power LEDs, low-cost PD, Arduino 1 as the LED driver, and USRP. The results showed an excellent alignment between simulation and real device experiment in terms of handover rate, delivered traffic per handover, and handover delay ratio. The final contribution of this thesis was presented in Chapter 5, which includes a vertical handover mechanism called CV2LC. Initially, we proposed a theoretical model for power consumption for the VLC and LTE networks, then we compared their performances in terms of energy efficiency, PRR, and latency. Last but not least, CV2LC uses VLC to transmit CAM and switches to LTE when VLC does not meet the reliability requirement. In terms of validation the CV2LC, represents a more stable performance in different scenarios in comparison to C-V2X and V2LC stand-alone.

Future Vision

The

1

 1 Manuscript outline . . . . . 5

Figure 1 . 1 :

 11 Figure 1.1: Wireless connections trend

Figure 1 . 2 :

 12 Figure 1.2: The applications of VLC in space, air, underwater, indoor, and car networks

Figure 1 . 3 :

 13 Figure 1.3: VLC platooning

  recherche en sciences et technologies du numérique (INRIA) Lille -Nord Europe" under the supervision of Dr. Valeria Loscri. During this research, I have participated in multiple academic activities including: • Enabling technologies for industrial Internet of things (21 July 2021 -28 July 2021) summer school at the University of Pisa, Italy • Vehicular Platooning (25 October 2021 -9 November 2021) Online course • Giving engaging scientific talks (28 October 2020 -30 October 2020) Online course • Français langue étrangère (FLE) -French language (07 February 2020 -17 April 2020) Université de Lille -DEFI -bât. SUP SUAIO -Cité scientifique • Ethique et intégrité scientifique -(27 Agust 2022) FUN MOOC, Université de Bordeaux Some parts of this research have been published as follows:

Figure 2 . 1 :

 21 Figure 2.1: Armada Beacon Hove, England [7]

Figure 2 . 2 :

 22 Figure 2.2: Photophone of A. G. Bell

Figure 2 . 3 :

 23 Figure 2.3: OWC technologies architecture

Figure 2 . 4 :

 24 Figure 2.4: Electromagnetic spectrum and visible light

Figure 2 . 5 :

 25 Figure 2.5: Single carrier intensity modulation techniques in VLC

Figure 2 . 6 :

 26 Figure 2.6: VLC transmission link including the major disturbance sources in outdoor and indoor applications. The optical wireless channel is affected by reflected interference.

Figure 2 . 7 :

 27 Figure 2.7:Underwater VLC in UTROV operation[START_REF] Latif | Visible light communication: Applications, architecture, standardization and research challenges[END_REF]

Figure 2 .

 2 8 represent schematics of V2X scenarios.

Figure

  Figure 2.8:Vehicle to everything communication scenarios[START_REF]C-V2X Scenario Simulations and Validation[END_REF]

Figure 3 . 1 :

 31 Figure 3.1: VLC front-end blocks

Figure 3 . 2 :

 32 Figure 3.2: VLC front-end orientation

Figure 3 . 3 :

 33 Figure 3.3: Link adaptive protocol flowchart

  V2LC Helperthe V2LC helper automatically implement the vlc-helper, channel-helper, and the Net-Device helper on the system. vlc-helper includes vlc-NetDeviceTx and vlc-NetDeviceRx that contains the main parameters of the VLC frontend such as transmitter optical power, angle of radiance, Lambertian order, concentration gain, FoV angle, etc. channel-helper, is derived from ns-3 point-to-point helper and connects the VLC channel to the Net-Device. On the other hand, Net-Device helper handles the connections between the node and the channel. It supports the link address and buffer-congestion control too. V2LC channel V2LC channel represents the optical characteristics of the outdoor vehicular VLC channel. The ns-3 point-to-point channel has been enhanced in[START_REF] Aldalbahi | Extending ns3 to simulate visible light communication at network-level[END_REF] to include the Lambertian propagation model. The current channel includes the statistical model of climate turbulence based on the pdf of

Figure 3 . 4 :

 34 Figure 3.4: ns3-V2LC module structure

Figure 3 . 5 :

 35 Figure 3.5: Generic V2LC scenario

Figure 3 . 6 :Figure 3 . 7 :

 3637 Figure 3.6: Bit error probability for different modulations

Figure 3 . 8 :

 38 Figure 3.8: Achieved goodput of LAP and slotted-aloha

Figure 3 . 9 :Figure 3 . 10 :Figure 3 . 11 :Figure 3 . 12 :Figure 3 . 13 :

 39310311312313 Figure 3.9: Adaptation sensitivity at 10 mps

Figure 4 . 1 :

 41 Figure 4.1: Handover Scenario

Figure 4 . 2 :

 42 Figure 4.2: Handover rate vs AP linear density with different speeds of the mobile entity.

Figure 4 . 3 :

 43 Figure 4.3: Average delivered data per handover vs AP linear density with different speeds of mobile nodes.

Figure 4 . 4 :Figure 4 . 5 :

 4445 Figure 4.4: General MAC frame 802.15.7 and the modified control field.

Figure 4 . 6 :

 46 Figure 4.6: Proposed VLC network architecture.

Figure 4 . 7 :

 47 Figure 4.7: Testbed configurations for performance evaluation, considering different

Figure 4 . 8 :Figure 4 . 9 :

 4849 Figure 4.8: Handover rate versus node density.

Figure 4 . 10 :

 410 Figure 4.10: Handover delay ratio versus node density.

Figure 5 . 1 :

 51 Figure 5.1: LTE-V2X resource structure

Figure 5 . 2 :

 52 Figure 5.2: LTE power consumption model

Figure 5

 5 Figure 5.3: Direct Conversion Transceiver Radio Architecture

Figure 5 . 4 :

 54 Figure 5.4: VLC power blocks

Figure 5 . 5 : 5 . 4 . 1 Figure 5 . 6 :Figure 5 .

 55541565 Figure 5.5: Point-to-point transmission model

  𝐵𝑃 𝑃𝐿(𝑑𝐵) = 22.7 • log 10 (𝑑) + 27.0 + 20.0 • log 10 ( 𝑓 𝑐 ) (5.20) • for 𝑑 ′ 𝐵𝑃 < 𝑑 < 5 𝐾𝑚 𝑃𝐿(𝑑𝐵) = 40.0•log 10 (𝑑)+9-16.2•log 10 (ℎ 𝐵𝑆 )-16.2•log 10 ℎ 𝑀𝑆 + 3.8 • log 10 ( 𝑓 𝑐 ) (5.21) • NLOS 𝑃𝐿(𝑑𝐵) = (44.9-6.65•log 10 (ℎ 𝐵𝑆 ))•log 10 (𝑑)+5.83•log 10 (ℎ 𝐵𝑆 )+15.38+23•log 10 ( 𝑓 𝑐 ) (5.22) The effective breakpoint distance 𝑑 ′

  SNR-based Adaptive Transmission (d) INR-based Adaptive Transmission

Figure 5 . 8 :

 58 Figure 5.8: Receiver Energy Efficiency VLC

Figure 5 . 9 :Figure 5 . 10 :

 59510 Figure 5.9: Receiver Energy Efficiency C-V2X

Figure 5 . 11 :

 511 Figure 5.11: Transmitter Energy Efficiency LTE-V2X

  SNR-based Adaptive Transmission (d) INR-based Adaptive Transmission

Figure 5 . 12 :

 512 Figure 5.12: Packet Reception Ratio

Figure 5 .

 5 Figure 5.13 demonstrates the packet reception ratio at the mobile nodes that are transmitting CAM packets using cellular long-term evolution Mode 3 and Mode 4. 4 curves show 4 different scenarios similar to vehicular VLC scenarios. The LTE-V2I has the best PRR performance in urban and highway scenarios regardless of the traffic density, owing to the wide coverage and reliable resource allocation strategy of LTE.In the next world, the packet reception ratio of V2V is smaller, due to the lower coverage range of onboard modules in the vehicles compared

Figure 5 . 13 :Figure 5 . 14 :

 513514 Figure 5.13: PRR C-V2X

5. 6

 6 represents the scenario where the mobile nodes rely on VLC technology to transmit their CAMs. The INR-based handover mechanism guarantees seamless horizontal handover inside VLC coverage. When the performance of the VLC link degrades, CAMs are sent through LTE radio access technology.Figure 5.15 shows CV2LC module implemented on ns-3 simulation tools.

Figure 5 . 15 :

 515 Figure 5.15: Transitions between V2LC and C-V2X modes are carried out in the flow switch based on each module's feedback

Figure 5 . 16 :Figure 5 . 17 :

 516517 Figure 5.16: Packet Reception Ratio in different scenarios of cellular vehicular VLC

Figure 5 .Figure 5 . 18 :Figure 5 . 19 :

 5518519 Figure 5.20 demonstrates the comparison of the above metrics in ad hoc and heterogeneous vehicular networks. The PRR, latency, and energy efficiency at the transmitter and the receiver of the two ad hoc V2X

  (a) Packet Reception Ratio [%] (b) Latency [ms] (c) Receiver Energy efficiency [Kbits/Joule] (d) Transmitter Energy efficiency [Kbits/Joule]

Figure 5 . 20 :

 520 Figure 5.20: Performance comparison of LTE-V2x, V2LC, and CV2LC

•

  Meysam Mayahi, Valeria Loscri, and Antonio Costanzo. 2021. Link adaptive protocol for V2LC. In Proceedings of the Workshop on Internet of Lights (IoL'21). Association for Computing Machinery, New York, NY, USA,13-17.

	Related Works 2
	https://doi.org/10.1145/3469264.3469807 • M. Mayahi, V. Loscri and A. Costanzo, "INVISIBLE: Enhanced Handover 2.1 VLC . . . . . . . . . . . . . 7 2.2 V2LC . . . . . . . . . . . . 10 technique for Vehicular Visible Light Networks," 2022 IEEE 95th Vehicular Tech-2.2.1 V2LC Challenges . . . . . 12 nology Conference: (VTC2022-Spring), 2022, pp. 1-5, doi: 10.1109/VTC2022-2.2.2 Previous Contributions . 14 Spring54318.2022.9860664. • M. Mayahi, A. Costanzo, V. Loscri and A. M. Vegni, "An Interference to 2.3 Conclusion . . . . . . . . . 16
	Noise Ratio Handover mechanism for Mobile Visible Light Communication
	Networks," 2022 13th International Symposium on Communication Systems,
	Networks and Digital Signal Processing (CSNDSP), 2022, pp. 457-462, doi:
	10.1109/CSNDSP54353.2022.9907915.

Table 2 . 1 :

 21 Performance metrics in different OWC technologies

	Metric	VLC	LiFi	OCC	FSO
	Topology	Unidirectional/Bidirectional	Bidirectional	Unidirectional Unidirectional/Bidirectional
	Coverage	20 m	10 m	60 m	≤ 10,000 km
	Mobility support	Low	High	Low	No
	Distortion source ambient light, atmospheric disturbance	ambient light	ambient light	atmospheric disturbance
	Interference level	Low	Low	Zero	Low
	Data rate	10 Gbps in LED and ≤ 100 Gbps in LD 10 Gbps in LED and ≤ 100 Gbps in LD	55 Mbps	40 Gbps
	Security	High	High	High	High

the pioneering work of Bapst and Gfeller in 1979. They showed the extraordinary capacity of OWC which is promising hundred of terahertz of bandwidth. The four main OWC technologies, namely visible light communication (VLC), Light Fidelity (LiFi), Optical Camera Communication (OCC), and Free Space Optics have different characteristics [9],

2.8: Vehicle to

	everything com-munication scenarios [22] Intelligent Transport System (ITS) uses different radio access technologies (RATs) to implement V2X communication. Here we discuss the popular RATs for V2V and V2I communications and after we give a summarized comparison in form of table 2.2.

DSRC, IEEE 802.11p: The

  primary radio access technology enabling V2X communication in a connected vehicle is DSRC. DSRC spectrum is locally allocated by national organizations, and standardized by the IEEE and the American Society for Testing and Materials International (ASTM) in the USA, the European Telecommunications Standards Institute (ETSI) and the European Committee for Standardization (CEN) in Europe, and the Association of Radio Industries and Businesses (ARIB) in Japan. To use the DSRC in the vehicular networks the IEEE 802.11p and Wireless Access in Vehicular Environments (WAVE) have been implemented as an amendment to IEEE 802.11 (IEEE 802.11a) standard in 2010 and revised in 2012 to facilitate V2V and V2I communication. The IEEE 802.11p includes DSRC based on ASTM E2213-03 standard, which specifies the Medium Access Control (MAC) sub-layer and the physical layer of the WAVE protocol stack. The IEEE 802.11p protocol is widely used in North America and Europe [23].

	Cellular V2X: The first standard of C-V2X is the release 14 from 3GPP
	in September 2016. It is an updated version of the LTE based device to
	device (D2D) communication ProSe introduced in 3GPP Release 12 which
	focuses on V2V

communication and later on by further enhancements to support V2I-based safety and non-safety service requirements. The D2D interface PC5 introduced in Release 12/13 was not suitable for V2X services and needs to be modified. Thus, to enable V2V commu- nication and address the two main challenges of a vehicular network

  : high-speed (up to 250Kph) and high density (thousands of nodes), the current interface is introduced in Release 14 with changes at the link and system level. This new design is scalable for different bandwidths namely 10 MHz and 20 MHz[START_REF] Gpp | Study on LTE-based V2X services[END_REF]. The C-V2X technology introduced two modes of vehicular communication.

Mode-3 provides the vehicle to infrastructure (base station) communication while Mode-4 allows

  the vehicles to communicate with each other directly

Table 2 .2: Vehicular

 2 radio access technologies, adapted from[5]

	Feature	DSRC	WiFi	LTE-V2X	5G-NR-V2X	VLC
	Standard	IEEE 802.11p	IEEE 802.11p	3GPP Rel 13/14	3GPP Rel 15/16	IEEE 802.15.7
	Frequency band	5.86 -5.92 GHz	2.4 GHz , 5.2 GHz	450 MHz -4.99 GHz	700 MHz , 3.6 and 26 GHz	380 -800 THz
	Bandwidth	10 MHz	20MHz	10 MHz, 20 MHz	400 MHz	400 THz
	Bit rate	3 -27 Mbps	6 -54 Mbps	≤ 1 Gbps	≤ 20 Gbps	11.67 kbps -96 Mbps
	Coverage range	≤ 1 km	≤ 500 meters	≤ 30 km	Ubiquitous	≤ 100 meters
	Mobility management	≤ 60 kmph	Low	≤ 350 kmph	≤ 500 Kmph	Low
	QoS support	EDCA a	EDCA	QCI and bearer selection	NA	NA
	V2X support	V2V Ad hoc, V2I	V2V Ad hoc, V2I	V2X via D2D, V2I	V2V, V2I	V2V, V2I
	Deployment	RSU	Hotspot, access point evolved NodeB (mode 3), ue (mode 4)	NSA and SA mode	Illumination infrastructure
	Market penetration	Low	High	High	Potentially high	Low
	Multicast support	Broadcast	Broadcast	eMBMS	Unicast, Broadcast, multicast	Unicast, Broadcast
	Latency	100 msec	50 msec	10-30 msec	≤ 1 msec	≃ 1 msec
	a Enhance Distributed Channel Access
			enhanced interoperability service in 5G-NR facilitates access to C-V2X
			technology too. The RATs performance in terms of security, infrastructure
			distribution, quality of service, and edge services have been significantly
			enhanced in 5G [26].
			WiFi: The smart city developments drive WiFi deployments in mobile
			devices excessively. WiFi uses unlicensed Industry, Science, and Medical
			(ISM) bands which carry more traffic than the cellular networks in the
			licensed bands. WiFi is one of the complementary and low-cost RATs to
			provide ITS services. The protocol stack of WiFi (IEEE 802.11a/b/g/n/ac)
			is not optimized for vehicular mobility context, however, various amend-
			ments to the IEEE 802.11 standard are bringing advancements in WiFi,
			such as assisted roaming support by IEEE 802.11k, Fast Basic Service
			Set Transition (FT-BSS) for fast roaming via IEEE 802.11r, better network
			performance with IEEE 802.11v, protection of management frames by
			IEEE 802.11w, and better bandwidth, security, and services-on-demand
			by Hotspot 2.0 based on IEEE 802.11u. These advancements make WiFi
			a potential and competitive candidate to provide seamless and secure
			vehicular connectivity [5].
			Vehicular VLC: Based on strict competition on traditional radio resources,
			the new technologies are more appealing to use alternative bands for
			vehicular communications. Today, visible light communication is of high
			interest to engineers and scientists. Unlike RF-based solutions (e.g., C-
			V2X, and DSRC), VLC has a less complicated structure, an unlicensed
			band, and represents a secured, power efficient, and reliable complemen-
			tary solution for vehicular RATs. VLC spectrum resides between 380
			and 800THz (380-780nm) and uses a directional LED-based transmitter
			for full-duplex communications [27]. Table 2.2 summarized the main
			features of the above-mentioned RATs.

  This chapter is dedicated to the fundamentals of the VLC channel model and the simulation module. A new ns-3 V2LC module is presented to simulate a real outdoor VLC channel. The channel model accounts for Lambertian path loss and climate distortion. It also proposes the Link Adaptive Protocol (LAP) where a single handshake association and fast handover algorithm prolongs the VLC connectivity. Under such a pragmatic channel model, the LAP aims to prolong the VLC connectivity as well as boost the transmission rate collaborative to the quality of the received signal represented in Signal to Noise Ratio (SNR). SNR represents a safe metric to allocate different modulation schemes once

3.1 Channel Model . . . . . . . 3.2 Link Adaptive Protocol . . 3.3 Simulation . . . . . . . . . . 3.4 Performance Analysis . . . 3.5 Conclusion . . . . . . . . . . it surpasses the threshold.

Detecting large enough SNR triggers the association in a single handshake mechanism to proceed in adaptive modulation transmission. LAP performance has been verified in terms of outage probability and goodput in addition to further analysis of protocol efficiency. Moreover, adaptive modulation has been suggested in order to increase the throughput. Simulation results show that LAP outperforms slotted-aloha in outage probability and goodput. It is also properly achieving a trade-off between pilot rate and protocol efficiency.

Table 3 .

 3

1: Outdoor illuminance range

Table 3 . 2 :

 32 Main parameters

	Parameter	Term	Value[unit]
	Boltzmann constant	k	1.3086𝑒 -23[𝐽/𝐾]
	Noise bandwidth factors 𝐼 2 , 𝐼 3	0.562 , 0.868
	Background power	𝑃 𝑏 𝑔	0.533[𝑚𝑊]
	Open-loop voltage gain	G	10
	FET transconductance	g m	30[𝑚𝑆]
	Fixed capacitance of PD	𝜂	112[𝑝𝐹/𝑐𝑚 2 ]
	Responsivity	r	0.2[𝐴/𝑊]
	Electric charge	q	1.60217𝑒 -19[𝐶]
	Equivalent noise b.w	B	3[𝑀𝐻𝑧]
	Absolute temperature	𝑇 𝑘	298[𝐾]
	FET channel noise factor	Γ	1.5
	Filter Transmission coef.	T 0	1
	Refractive index	n	1.5
	Number of LEDs		1
	Input voltage		4.5[𝑉]
	Data packet size		536[𝐵𝑦𝑡𝑒 𝑠]
	Pilot size		10[𝐵𝑦𝑡𝑒 𝑠]
	moves to other links when the quality of the current link degrades. As
	shown in flowchart 3.3, the model includes 3 steps, naming: Scanning,
	Association, and Transmission.

Initially, the transmitter investigates the VLC environment by sending a tiny control message called pilot every 𝑇 𝑝 seconds. The receiver at the same time, estimates the SNR, by the received signal power during 𝑇 𝑝 based on 3.13.

  The proposed module includes the VLC channel model with two types of channel impairments (i.e., ℎ 𝐿𝑎𝑚 and ℎ 𝑐𝑙𝑚 ) as it is discussed earlier. The figure3.4 represents the ns3-V2LC module structure. NS3-V2LC includes 4 objects: • V2LC helpers, • V2LC channel, • performance model, and • mobility model.

	the VLC module proposed in [56]. The extension includes the patch to
	the most recent version of ns-3.33, as well as the integration to the SUMO
	mobility model. Simulation of Urban MObility (SUMO) is a free and
	open-source traffic simulation suite. It is available since 2001 and allows
	the modeling of inter-modal traffic systems -including road vehicles,	• It supports different libraries • It can be integrated to the external
		software

public transport, and pedestrians. SUMO is a wealth of supporting tools that automate core tasks for the creation, execution and evaluation of traffic simulations, such as network import, route calculations, visualization and emission calculation. SUMO can be enhanced with custom models and provides various APIs to remotely control the simulation

[START_REF] Memedi | Impact of Vehicle Type and Headlight Characteristics on Vehicular VLC Performance[END_REF]

.

Table 3 . 3

 33

: Modulation table rising up to 𝛼. Instantly, node1 associates with node3 and repeats the previous process.

  The wide use of light emitting diode (LED) in cars and roadside units is encouraging the exploitation of the Visible Light Communication (VLC) paradigm in vehicular applications. However, real scenarios are characterized by poor Signal-to-Noise Ratio (SNR) conditions and, heavy interference among devices in the same area, which make effective handover operations critical for properly supporting mobility. A novel approach called Interference based haNdover mechanism for VISIBle Light nEtworks (INVISIBLE) to perform handover in Vehicular Visible Light Networks, based on the evaluation of Interference to Noise Ratio (INR) and Interferer to Interference (IIR) Ratio, is proposed in this chapter, in place of the conventional approaches based on SNR evaluation. Our approach has been numerically validated, taking into account the Adaptive Modulation Scheme (AMS) and a VLC device moving at different speeds. Furthermore, a comparison with the SNR-based approach has been provided. Simulation results show how the INR-based handover mechanism outperforms SNR-based handover in terms of handover rate, the average delivered data per handover and handover delay ratio.

	Handover Mechanism 4
	4.1 V2LC Handover . . . . . . .
	4.2 System model . . . . . . . .
	4.3 Simulation Analysis . . . .
	4.4 Small-scale Implementation
	4.5 Experimental Validation .
	4.6 Conclusion . . . . . . . . . .

table 4

 4

	𝛼	Modulation scheme Relative bitrate	𝑑 𝑚𝑎𝑥
	11.14[𝑑𝐵]	OOK	100[𝐾𝑏𝑖𝑡/𝑠]	12.5[𝑚]
	11.3[𝑑𝐵]	4PSK	150[𝐾𝑏𝑖𝑡/𝑠]	12.0[𝑚]
	18.4[𝑑𝐵]	8PSK	200[𝐾𝑏𝑖𝑡/𝑠]	8.0[𝑚]
	20.6[𝑑𝐵]	16PSK	250[𝐾𝑏𝑖𝑡/𝑠]	6.5[𝑚]

.1

[START_REF] Song | Performance Analysis of the IEEE 802.11p Multichannel MAC Protocol in Vehicular Ad Hoc Networks[END_REF]

. If the system was recognized as interference dominated (i.e. 𝐼𝑁 𝑅 𝑡 ≥ 10), then it is possible to search for the dominant interferer using 𝐼𝐼𝑅. Dominant interferer could be

Table 4 .

 4

	1: Modulation table

Table 4 .

 4

	[1/𝑚𝑖𝑛]	(4.11)

constant in dense AP distribution. The INR-based handover algorithm, in fact, always selects the AP which provides the largest 𝑡 𝑠 . The largest sojourn time is when the distance between the ME and the AP is less than 𝑑 𝑚𝑎𝑥 and it is represented by the farthest AP which stands at most 𝑑 𝑚𝑎𝑥 meter from the ME.

  𝑑𝑒𝑙𝑎𝑦 𝑟𝑎𝑡𝑖𝑜 = bits in the control frame of Figure4.4 is used to specify the velocity of the mobile node, as well as 𝑑 𝑚𝑎𝑥 of each LED rather than the number of interferers 𝑁 for the INR-based mechanism. The required time to perform a handover is the handover frame size (i.e., 𝐻𝑂 𝑓 𝑟𝑎𝑚𝑒 𝑠𝑖𝑧𝑒 [bits]) over the bitrate at both the transmitter and the receiver (i.e.,1 𝑅 𝑏 (𝑀) =

	𝐻𝑂 𝑑𝑒𝑙𝑎𝑦	× 100,	(4.12)
	𝑡 𝑠
	𝐻𝑂 1 𝑅 𝑏,𝑡𝑥 (𝑀) +	1 𝑅 𝑏,𝑟𝑥

𝑑𝑒𝑙𝑎𝑦 = 𝑡 𝐻𝑂 𝑟𝑒 𝑞 + 𝑡 𝐻𝑂 𝑟𝑒𝑠 , (4.

13)

with 𝑡 𝐻𝑂 𝑟𝑒 𝑞 and 𝑡 𝐻𝑂 𝑟𝑒𝑠 defined as the time necessary to • make an handover request and •• provide an handover response, respectively. Assuming the same frame size used for handover request and handover response (i.e., 𝑡 𝐻𝑂 𝑟𝑒 𝑞 = 𝑡 𝐻𝑂 𝑟𝑒𝑠 ) included in the MAC frame format specified by IEEE standard for short-range wireless optical communication using VLC 802.15.7

[START_REF]IEEE Standard for Local and Metropolitan Area Networks-Part 15.7: Short-Range Wireless Optical Communication Using Visible Light[END_REF]

, the reserved

Table 4 .

 4

	11.14	OOK	100	20
	11.3	4PSK	150	16
	18.4	8PSK	200	12
	20.6	16PSK	250	8.5

[dB] Modulation scheme (M) Relative bitrate [kbps] 𝑑 𝑚𝑎𝑥 [cm] 3: Modulation table

Table 4 . 4

 44

	: Main parameters	Parameter	Value[unit]
		Responsivity, 𝑟	0.2 [A/W]
		Area of PD , A	1.3 [𝑐𝑚 2 ]
		Minimum Transmission time, 𝑇 𝑐	200 [ms]
		Sampling Time, 𝑡 𝑖	100 [ms]
		Half power semi-angle, 𝜙 𝑚𝑎𝑥	35 •
		Linear AP density, 𝜌 𝑙	[1, 10] [m -1 ]
		Minimum IIR, 𝛽	0.3
		INR-based HO frame size	39 [Bytes]
		SNR-based HO frame size	28 [Bytes]
		Number of LEDs	5
		Number of PDs	4
		Input electrical power	1.0 [W]
		Number of simulations	30
		Duration of each simulation	100 [s]
		Rounds of each simulation	10

  .8, we compare the handover rate (i.e., 𝐻𝑂 𝑟𝑎𝑡𝑒 [𝑚𝑖𝑛 -1 ]) obtained with the INR-based and the SNR-based handover schemes, for different speeds. It can be shown that the handover rate has a reverse relationship with the average connection time 𝑡 𝑠 [𝑠] as follows 4.11Regarding the excellent matching between the simulation and the testbed results, it is admitted that at the same speed as the AP density increases, the SNR-based handover rate increases linearly. According to equation (4.10) and (4.11), going from lower to higher 𝜌 𝑙 , the distance between node 𝑃𝐷 (Rx) and node 𝑖 (Tx) is decreasing. Since 𝑑 𝑚𝑎𝑥 and 𝑉 𝑃𝐷 are fixed, the average connection time declines accordingly, and as a result

the handover rate increases. On the other side, the INR-based handover rate increases in the sparse AP deployment and saturates in the dense AP distribution. At the dense AP installation (𝑋 𝑃𝐷 -𝑋 𝑖 ≤ 𝑑 𝑚𝑎𝑥 ) the longest 𝑡 𝑠 is determined by the farthest AP which stands at most 𝑑 𝑚𝑎𝑥 meter far from the mobile node. Higher velocity corresponds to a lower connection

  Enhanced Handover Technique for Vehicular Visible Light Communication Networks INVISIBLE, based on Interference to noise ratio and Interferer-to-Interference ratio, has been proposed and validated through simulations, using the software NS3 and the experimental tests. A comparison between our technique and the conventional technique based on SNR has been provided in terms of handover rate, average delivered data per handover and handover delay ratio. The results in both simulation and experimental tests show how the proposed technique avoids useless handovers, and by consequence, considerably improves the average delivered data per handover and reduces the amount of overhead information in the network. At the same time, our technique shows a significantly reduced handover delay ratio, in comparison with the SNR-based technique, in dense scenarios. Since the latter aspect is frequent in vehicular network architectures with a high number of users, this handover policy could be easily applied in most realistic scenarios.

	Cellular Vehicular Visible Light Communication 5
	In this chapter, the cooperation of Visible Light Communication (VLC)	5.1 C-V2X . . . . . . . . . . . .
	and the long-term evolution (LTE) cellular network in vehicular commu-	5.2 LTE Power Consumption
	nication is discussed. The advantages of V2LC over C-V2X have been	5.3 VLC Power Consumption
	studied in detail to clarify the motivation for using VLC over cellular networks in vehicular communication. The metrics that have been con-	5.4 Energy Efficiency . . . . . 5.4.1 Performance analysis: VLC
	sidered in this study are energy efficiency, latency, and packet reception	vs. LTE . . . . . . . . . . . .
	ratio. Moreover, a new power consumption model has been defined in	5.5 CV2LC . . . . . . . . . . . .
	this chapter to measure the power efficiency of each technology. Finally,	5.5.1 Simulation Results . . . . .
	we propose a Cellular Vehicular VLC (CV2LC) protocol for adaptive vertical handover between VLC and LTE in vehicular scenarios. This	5.6 Conclusion . . . . . . . . .
	protocol meets the 3GPP baseline for Cooperative Awareness Messages
	(CAM) safety massages in different traffic densities.
	Vehicle to everything (V2X) applications are supported by radio access
	technology (RAT) standards such as IEEE 802.11p (i.e., DSRC or ITS-G5)
	and Cellular V2X (i.e., LTE-V2X). LTE-V2X is an LTE (long-term evolution)
	adaptation for vehicular scenarios standardized by 3GPP, under released
	14 and 15. It is based on the PC5 or sideline LTE radio interface. It
	supports distributed V2V and V2I communications, using Mode 3 and
	Mode 4 respectively, which do not require cellular infrastructure support,
	so it is interesting for ubiquitous ad-hoc networks. LTE however, faces
	strict challenges in handling aperiodic messages of different sizes due to
	the sensing-based Semi-Persistent Scheduling (SPS) scheme and these
	challenges can not be resolved by different configurations of LTE. SPS
	scheme causes further issues in vehicular communication such as:
	1. High traffic and power consumption LTE-based Cellular Vehicle-
	To-Everything (C-V2X) allows vehicles to communicate with each	LTE-V2X and C-V2X have been used in-
	other directly without the need for infrastructure and is expected	terchangeably in this study
	to be a critical enabler for connected and autonomous vehicles.
	V2X communication-based safety applications are built on the
	periodic broadcast of basic safety messages with vehicle state
	information. Vehicles use this information to identify collision
	threats and take appropriate countermeasures. As the vehicle
	density increases, these broadcasts can congest the communication
	channel resulting in increased packet loss, fundamentally impacting
	the ability to identify threats without delay. To address this issue,
	it is important to incorporate a congestion control mechanism.
	Congestion management scheme based on rate and power control
	has proved to be effective for DSRC [65].
	2. Mobility Management (MM) in Long-Term Evolution (LTE) net-
	works is a vital process to keep an individual User Equipment (UE)
	connected while moving within the network coverage area. MM
	Entity (MME) is the LTE component responsible for tracking and
	paging procedures and controlling the corresponding signaling

between the UE and its serving cell, which is necessary for datapacket exchange. Because of the massive increase in the density of mobile UEs, MME is burdened by the high volume signaling load, especially because most of that load comes from Tracking

  𝑃 𝑉 𝐶𝑂 is nominal power consumption at voltage-controlled oscillator, 𝑃 𝐼𝑄 𝑚𝑜𝑑𝑢𝑙𝑎𝑡𝑜𝑟 is the in-phase and quadrature modulators power consumption, and 𝑃 𝐶𝑙𝑜𝑐 𝑘 is the power needed for clock generation and buffering in[mW]. On the other hand, the power consumption of the

	The amplified and filtered BB
	analog signals in the I and Q channels are converted into digital signals by
	analog-to-digital converters (ADC), and the digital signals pass through
	digital filters to further suppress nearby interferers and enhance the
	channel selectivity.
	Compared with the receiver, the direct-conversion transmitter has fewer
	issues, and it is relatively easy to be implemented. The I and Q BB signals
	coming from the transmitter DAC converters first pass through low-pass
	filters to make the adjacent channel and alternate channel emission levels
	further suppressed and to eliminate aliasing products. The filtered and
	amplitude attenuated I and Q BB signals both are directly up-converted
	to RF signals, and then they are added together by an I/Q modulator.
	The composite RF signal is amplified all the way up to the RF power
	amplifier (PA).
	The power consumption of the transmitter ASP can be modeled as 5.8,
	considering only the aggressive power consumer components of the
	direct conversion transmitter:
	𝑃 𝐴𝑆𝑃,𝑇𝑥 = 𝑃 𝐼𝑄 𝑚𝑜𝑑𝑢𝑙𝑎𝑡𝑜𝑟 + 𝑃 𝐶𝑙𝑜𝑐𝑘 + 𝑃 𝑉 𝐶𝑂	(5.8)
	in 5.8,

  𝐸 𝑇𝑥 = 𝑃 𝑇𝑠 • 𝐷 𝑠 + 𝑃 𝑇𝑖 • 𝐷 𝑖 + 𝑃 𝑇𝑡 • 𝐷 𝑡 (5.13) 𝐸 𝑅𝑥 = 𝑃 𝑅𝑠 • 𝐷 𝑠 + 𝑃 𝑅𝑖 • 𝐷 𝑖 + 𝑃 𝑅𝑟 • 𝐷 𝑟 (5.14) where 𝐷 𝑥 is the time spent in state 𝑥, and 𝑝 𝑥 is power consumed in state 𝐸 𝑇𝐵𝐵 + 𝐸 𝑇𝑅𝐹 , 𝐸 𝑇𝐵𝐵 = 𝑎 • 𝑅 𝑏 • 𝐷 , 𝐸 𝑇𝑅𝐹 = 𝑏 • 𝑃 𝑡 • 𝐷 (5.15) 𝐸 𝑅𝑥 = 𝐸 𝑅𝐵𝐵 + 𝐸 𝑅𝑅𝐹 , 𝐸 𝑅𝐵𝐵 = 𝑐 • 𝑅 𝑏 • 𝐷 , 𝐸 𝑅𝑅𝐹 = 𝑝 𝑅𝑅𝐹 • 𝑅 𝑏 • 𝐷 (5.16) 𝑎, 𝑏, 𝑐 are coefficients that depend on the technology. Energy Efficiency Finally, energy efficiency is formalized as the ratio of delivered data in a given throughput to the energy consumption in one TTI. 𝐸𝐸 = 𝑅 𝑏 • 𝑍/𝐸 𝑇𝑇𝐼 [𝑏𝑖𝑡/𝐽𝑜𝑢𝑙𝑒]

	𝐸 𝑅𝑥	(5.12)
	𝑥.
	s: sensing, i: idle, t: transmission, r: reception
	The energy consumption at the transmitter and the receiver can be
	re-formed as 5.15 and 5.16
	𝐸 𝑇𝑥 =

  •• Smaller base stations can work from a lower supply voltage, further reducing their consumption. All RF components' powers are downscaled based on the constraining space and different hardware implementations of smaller cells.

		Scaling of RF
	power with input parameters is done as follows. All RF sub-components
	have a scaling exponent of 1 with respect to the number of antennas
	and time-domain duty cycling. For carrier and clock generation sub-
	components, scaling exponents have the value zero. For the other RF
	sub-components, the scaling exponent is 1 with respect to frequency-
	domain duty-cycling, assuming a scalable implementation. Technology
	scaling is used for analog, too, based on a scaling factor as a function
	of the selected CMOS technology compared to the reference tech = 65
	nm case. 5.19 is an empirical rule from the designer's experience, not a
	physical law:
	𝐷𝑜𝑤𝑛𝑠𝑐𝑎𝑙𝑖𝑛 𝑔 𝑓 𝑎𝑐𝑡𝑜𝑟 = 𝑃𝑜𝑤𝑒𝑟(65 𝑛𝑚) 1 +	𝑡𝑒 𝑐 ℎ/65 -1 2	(5.19)

  5 𝑚 for V2I communications.

	Analogue Item Power Consumption [mW]
	IQ Modulator	1000
	VCO	170
	Clock	990
	LNA	300
	Attenuator	10
	Dual Mixer	1000
	PA	650

Table 5 . 1 :

 51 LTE Analogue Major component's Power Similarly, table 5.2 shows the power consumption of the VLC components used in the proposed energy model. The street light poles have been used as VLC infrastructure based on global lighting design guidance

Table 5 . 2 :

 52 VLC analog power specification

  In general 8 cases have been analyzed to compare the performances in PRR, latency, transmitter EE, and receiver EE. The horizontal axis contains the scenario cases including urban V2I high density, urban V2V high density, highway V2I high density, highway V2V high density, urban V2I low density, urban V2V low density, highway V2I low density, and highway V2V low density. On the other side, the vertical axis stands for the range of represented metrics. For instance, in figure5.20a the PRR of CV2LC is always above the 95 percent while the V2LC is below this range in 2 cases: highway V2I high the 3GPP threshold for CAM reception rate density and highway V2I low density. Specifically, in these two cases the CV2LC use only the LTE network to disseminate its CAMs, so the PRR of CV2LC is equal to C-V2X in these cases. In the other scenarios, the performance of CV2LC is lower than C-V2LC in terms of PRR, just because when both networks ( VLC and LTE) are available, CV2LC chooses VLC for CAM transmission which in return has a lower PRR than C-V2X. The latency performance of CV2LC is compared with the other two standalone networks (C-V2X and V2LC) in figure5.20b. The latency of the CV2LC is considerably decreased in comparison with LTE, while it is bigger than VLC latency. The difference in latency is due to the different channel access regulations in V2LC and LTE. As it was discussed in

  CV2LC mechanism proposed in Chapter 5 was optimised for safety application traffics which should comply with a certain PRR threshold. More efficient vertical HO may integrate several application traffic types including safety and non-safety traffic. Considering various data traffic types, QoS requirement could be different. For instance, multimedia traffic requires larger bandwidth compared to voice call traffic, with different latency red lines. Although, in this thesis we attempted to include all the important components in the power model, but experiments are necessary to achieve a more precise power model. Including real device implementation in future works will enhance the accuracy of the current model and validate it for other research activities. Eventually, adaptive coding schemes could increase the robustness of the VLC in outdoor environments and prolong the coverage range. Integrating different coding rates into the adaptive modulation scheme is the highest priority of future work. Adaptive modulation and coding scheme (AMC) will increase the throughput and spectrum efficiency. In-phase and Quadrature. 51IFIntermediate Frequency. 51 IIR Interferer to Interference Ratio. 4 IM Intensity Modulation. 1 IM/DD Intensity Modulation and Direct Detection. 1 INR Interference to Noise Ratio. 4 INRIA Institut national de recherche en sciences et technologies du numérique. 5 INVISIBLE Interference based haNdover mechanism for VISIBle Light nEtworks. 4, 29, 34, 69 IR Infrared. 8 ISM Industry, Science, and Medical. 12 ITS Intelligent Transportation system. 2

	FEC forward error correction. 60
	FLE Français langue étrangère. 5
	FoV Field of View. 2
	FSO Free Space Optical. 7
	FT-BSS Fast Basic Service Set Transition. 12
	G
	Gbps Gigs bits per second. 8
	GHz Giga Hertz. 11
	GOPS Giga operations per second. 57
	GOPS/W Giga operations per second per watt. 50
	H
	HO Handover. 33, 70
	I
	I/Q K
	Kmph Kilometer per hours. 12
	L
	LANET visible-Light ad-hoc network. 15
	LAP Link Adaptive Protocol. 4, 17
	LD Laser Diode. 8
	LED Light Emitting Diode. 1
	LiFi Light Fidelity. 8
	LNA low noise amplifier. 51
	LoS Line of Sight. 2
	M
	M2M Machine-to-Machine. 1, 10
	D MAC Medium Access Control. 3
	D2D Device to Device. 3 Mbps Mega bits per second. 12
	DAC Digital to Analog Converter. 49 MCS Modulation and Coding Scheme. 46
	DCO-OFDM Direct Current biased Optical OFDM. 1 ME Mobile Entity. 30
	DD Direct Detection. 1 MHz Mega Hertz. 11
	DL Downlink. 49 MM Mobility Management. 45
	DSP Digital Signal Processing. 49 MME MM Entity. 45
	DSRC Dedicated Short Range Communication. 2, 3 msec millisecond. 12
	E N
	eNB evolved NodeB. 12 NS-3 Network Simulator Version 3. 4
	ETSI European Telecommunications Standards Institute. 11
	O
	F OCC Optical Camera Communication. 8