Artem A Nazarenko

Luis M Camarinha-Matos

Mechanisms for Service Composition in Collaborative Cyber-Physical Systems

Keywords: Collaborative Cyber-Physical Systems, collaborative services, system design

Recent advances in the IoT and Cyber-Physical Systems (CPS) enabled the possibility to combine capillary services or even services from different domains, such as smart home, smart city, smart infrastructure, etc. Thus, it is possible now to talk about the collaborative IoT or collaborative CPS, where services are not isolated from each other, but collaboratively offer added value and should provide advanced mechanisms for conflict resolution. However, still more efforts are needed to explore the ways of how capillary services might be selected and combined in an automated or semi-automated way forming composed or collaborative services. This process includes various stages, such as identification of selection criteria, discovery, negotiation, etc., that need to be considered from the very beginning of the system's design. For this reason, we propose an ontology that addresses issues related to various collaborative aspects of service composition. Moreover, we discuss the composition of services or coalition formation principles with advanced mechanisms for negotiation and conflict resolution considering, for instance, the access rights and ownership.

Introduction

With the progress of the Industry 4.0 development, the Cyber-Physical Systems (CPS) have been adopted in many areas of human activities, such as home and industrial process automation, healthcare, smart agriculture, etc. According to [START_REF] Frank | Industry 4.0 technologies: implementation patterns in manufacturing companies[END_REF] the current industrial stage presumes deep integration between the operational systems and information and communication technologies (ICT). It is important to understand the processes and main drivers behind this trend. The drivers can be split into social and economic, as well as technological. Examples of social and economic ones are [START_REF] Lasi | Industry 4.0[END_REF]: (i) short development periods, (ii) individualization of demand, (iii) flexibility, (iv) decentralization, and (v) resource efficiency. The technological drivers include: (i) further automation of various manufacturing processes, (ii) digitalization and networking, (iii) miniaturization, and (iv) increased availability of electronic components. In other words, the new CPS are not isolated and single problem focused, but rather encompassing multiple aspects and addressing complex systems [START_REF] Frank | Industry 4.0 technologies: implementation patterns in manufacturing companies[END_REF].

Thus, a Complex CPS can be represented as an ecosystem that is composed of tens or hundreds of heterogeneous entities collaborating with each other in order to provide composed services. The modeling of IoT / CPS elements is well known and can be advantageous in multi-owners' landscape [START_REF] Gonçalves | A Collaborative Cyber-Physical Microservices Platformthe SITL-IoT Case[END_REF]. These elements or entities can be both of technical nature, such as sensors and actuators, as well as social nature as represented by human users. The human users can be at the same time the service consumers and the service owners, or the owners of several devices involved in the service provision. Effective support to these complex relations raises the need to introduce collaborative mechanisms for the orchestration of the involved CPS entities. In this regard, we can speak now of Collaborative CPSs that are characterized by "jointly acting and sharing information, resources and responsibilities in order to achieve a common goal" [START_REF] Nazarenko | Towards collaborative Cyber-Physical Systems[END_REF]. Thus, the CCPSs, contrary to ordinary CPS, lay larger emphasis on increased connectivity, collaboration, and distributiveness, allowing them to enrich their functionality. Moreover, we can differentiate between the internal collaborative entities -coming from within the considered CPS, and external collaborative entities -coming from the outside. Both the internal and external entities are part of a CCPS environment.

In this context, to deliver a composed service, a CCPS has to allocate the needed competencies and thus discover the components that will be able to provide the necessary functionality. The process of service composition can be compared to the process of coalition formation [START_REF] Barata | Coalitions of manufacturing components for shop floor agility -The CoBaSA architecture[END_REF]. The collaborative mechanisms are tightly interrelated with service composition aspects. The main purpose of a service is to satisfy the users' needs through allocation of required capabilities. In general, and in addition to interoperability issues, the process of services composition can face significant obstacles that can arise due to possible conflicts. One example could be, if different users with equal access rights attempt at acquiring the same service at the same time and in the same location / using the same resources. The mechanisms for conflict resolution should be introduced right from the design phase of the Collaborative CPS. Another challenge is to define how different constituents of the Collaborative CPS are interrelated.

In this work, we address these two challenges. Thus, the main research question guiding the work is:

What could be a suitable set of models and organizational structures to support the design of increasingly complex and evolving CCPSs? However, the current work addresses only some aspects of the general question formulated above. Thus, we can formulate the guiding research sub-questions for this particular paper as:

What could be a suitable upper ontology to represent the service-centric model of a CCPS? What can be a set of reasoning mechanisms to support collaborative service composition in CCPS?

In the proposed solution, conflict resolution mechanisms are introduced as Prolog rules, and to map different Collaborative CPS concepts we provide an ontology covering the identified critical aspects. A prototype development is then discussed.

Contribution to Digitalization and Virtualization

Digitalization can be defined as the process of applying digital technologies [START_REF] Ritter | Digitization capability and the digitalization of business models in business-to-business firms: Past, present, and future[END_REF] and is often interlinked with other terms such as digitization and digital transformation. However, the digitization term is more specifically used to describe the process of moving from analogue to digital data representation, while digital transformation is often seen as process of "restructuring economies, institutions and society on a system level" [START_REF] Rachinger | Digitalization and its influence on business model innovation[END_REF]. The notion of digital transformation can be also applied at the technological level addressing the evolution of legacy systems [START_REF] Osório | Open and Collaborative Micro Services in Digital Transformation[END_REF], i.e., the effects of digitalization on characteristics and performance of existing systems. In the context of our work, digitalization is considered as a corner stone due to the need to address the integration of the designed system with other important drivers of digitalization, such as Machine Learning and Automated Reasoning in general.

In this regard virtualization can be seen as an important part of the digitalization process. The notion of virtualization refers to a set of technologies enabling abstraction of underlying resources, while providing a logical view of resources [START_REF] Yu | Virtualization for Distributed Ledger Technology (vDLT)[END_REF]. Implementation of virtualization technologies can significantly improve the performance, facilitate system evolution, and improve system management through representing physical resources in more suitable form for processing. This paper addresses some aspects of virtualization, namely logical representation of physical resources. In this case, physical resources are, for instance, sensors and actuators and services are their logical representations. Virtualization of a CPS can be expressed at various complexity levels, from simple approaches where only a small part of the physical world is depicted, to more complex approaches or digital twins, providing a high level of computational and graphical identity of a CPS or a process [START_REF] Martins | Shop Floor Virtualization and Industry 4.0[END_REF]. This work contributes to this complex perspective.

Design Framework for the Proposed Solution

The proposed solution is based on the Collaborative CPS design framework previously described in [START_REF] Nazarenko | The Role of Digital Twins in Collaborative Cyber-Physical Systems[END_REF]. The framework includes three pillars: (i) Application Domain, (ii) CCPS Design, (iii) Knowledge Base, as inspired by the design science research paradigm. The application domain delivers all relevant information about the domain, such as spaces, users, roles, physical environment peculiarities, etc., where the designed system is going to be deployed. This information is derived from the domain specific scenario and is used as an input for the Collaborative CPS design phase.

During the design phase, the input information from the Application Domain is formalized to create a virtual abstraction of the physical environment. During this stage a designer can form the future system from the available functional building blocks. The process of formalization is supported through ontologies and taxonomies stored within the Knowledge Base. For instance, taxonomies can represent the details of a specific application domain, so that the designer can select the appropriate one, allowing the design tool to stay domain agnostic. The rules, available from the Knowledge Base, specify many aspects of the system behavior, for instance determining the conflict resolution or service composition principles. Moreover, the formalized models of key concepts to be used in the Collaborative CPS are available in the Knowledge Base. In terms of practical implementation, we adopted the following tools: Python environment for the Collaborative CPS design phase, Neo4j graphical database and Prolog engine for the Knowledge Base implementation. The Collaborative CPS design framework is illustrated below: The aforementioned tools were selected due to a set of reasons. First the Prolog engine provides powerful querying and reasoning capabilities and the PySWIP library allows for querying from within a Python program. Python is a suitable environment for the Collaborative CPS design pillar, enabling simple integration of various functional modules. And finally, the Neo4j, that is a graph-oriented database, is suitable to store different taxonomies, as well as to provide functionalities to track and define the ties between different components of the designed system. In other words, the graph-based approach allows identifying the strength of connections between the different nodes. For instance, during the operation phase, different devices can support a composed service for a limited time, so that they are connected and every time they build a coalition with the same devices the value of connection will change/increase.

Ontology

Ontologies are helpful for a wide variety of tasks in the process of CPS design. One example is the task of IoT/CPS system's configuration at the system level [START_REF] Perera | Semantic-Driven Configuration of Internet of Things Middleware[END_REF]. In the mentioned publication, the ontology proposed by the authors represents the structure or main concepts of sensor configuration mechanisms implemented in the CASCoM solution. This ontology, however, is purely focused on the sensor configuration tasks, without tackling the actuators and only slightly touching the high-level abstraction aspects.

Independently of various forms and types, ontologies include a vocabulary of concepts with definitions and the structure on how these concepts are interrelated, limiting the possible interpretations of the concepts in the modeled area [START_REF] Hildebrandt | Ontology Building for Cyber-Physical Systems: Application in the Manufacturing Domain[END_REF]. In other words, the general characteristics specific to every ontology are: the vocabulary of concepts that are explicitly defined and the way they are formed into a connected graph. For the specific area of Collaborative CPS design, an ontology addressing the core concepts and relationships among them can be used by a designer to implement the system's layout. This allows for the designer to be focused on the system's functionality and service design, rather than on implementation of basic building blocks supporting the above mentioned process.

In our ontology we intentionally ignore some data processing aspects, such as, for instance, measurement accuracy or quality in order to not overload the ontology, but still be able to demonstrate how the high-level concepts wrap up lower-level details including sensors, actuators, state, etc. Another significant issue with many Ontologies is the problem that they are too domain specific [11]. In the proposed Ontology we tried to stay domain agnostic to some extent.

Fig. 2. Excerpt of a Collaborative CPS Service Ontology

The ontology building process is partially based on the approach described in [START_REF] De Nicola | A lightweight methodology for rapid ontology engineering[END_REF]. The first step implies the definition of terminology characterizing the observed domain. During the next step the analysis of available ontologies that, for instance, are developed and provided by W3C, is accomplished. The following step involves definition of the textual description for the terms selected during the first step or the import of the textual descriptions for the terms used from the W3C ontologies. On the next stage the domain terms that have parent-child (subClassOf) relations are organized in a Taxonomy, similarly to the ISA (is-a) hierarchy. Followed by parthood or excretion of meronymy to establish connections of complex terms to their sub-components. Finally, the last step includes ontology composition.

The proposed Ontology -Collaborative CPS Service Ontology (CCSO) -is an ontology explicitly identifying the aspects intrinsic to the process of collaborative service establishment in a CPS ecosystem. The high-level concepts of the ontology are the Smart Environment and the Smart Community. The Smart Environment is the abstraction addressing the technical aspects of the designed system that is used to describe the surrounding enriched with sensing, actuating, and computing capabilities with increased contextual awareness and extended interaction capabilities [START_REF] Nazarenko | Basis for an Approach to Design Collaborative Cyber-Physical Systems[END_REF]. The Smart Community, on the other hand, is the abstraction defining the group of human users sharing common interests, preferences, and resources that are having a common social bond. The proposed ontology also includes elements of other well-known ontologies, such as Privacy Preference Ontology (PPO) [START_REF] Sanchez | Semantic-based privacy settings negotiation and management[END_REF] and IoT-lite [START_REF]IoT-Lite Ontology[END_REF]. The PPO contains the notion of "Operator" [START_REF] Sanchez | Semantic-based privacy settings negotiation and management[END_REF] that can be used for the rules design of the planned services. Another ontology used is the IoT-lite which offers, for instance, the notions of the sensor, actuator and device [START_REF]IoT-Lite Ontology[END_REF] -the underlying definitions for the Smart Environment. Thus, the IoT-Lite is the IoT specific ontology for managing data that covers some important low-level aspects of the design process.

The CCSO ontology considers the following aspects: -Assuming that every "Device" provides a "Service", thus device and service are related.

-"Device" can be of several types (mostly sensors and actuators, however, not only) -"Sensor" measures certain "Value" within the environment.

-The "Value" is associated to "Attribute". According to [START_REF]IoT-Lite Ontology[END_REF], "Attribute" is some property of an object (e.g. temperature, humidity, etc.) -On the other hand, "Actuator" has a "State" (e.g., on/off, open/closed, etc.).

-Both "Value" and the "State" are related to "Attribute".

-A particular case of object that has an "Attribute" is the "Smart Environment".

-"Smart Environment" has an associated physical "Location".

-Moreover, every "User" has certain "Location" within the system (that might be changed). -Every "Device" is owned by a "User".

-Every "User" belongs to a "Smart Community", within which he/she has a "Role". -Every "Role" affects the "Access right" in certain way.

-"Access right" affects the access to a "Service".

-A set of "Services" can be combined into a "Composed Service/Coalition" -"Composed Service/Coalition" is of a certain type (e.g., Health, Entertainment, Comfort). -Moreover, it possesses a set of "Metrics" to assess the service.

-It also has a set of "Tasks". The notion of a "Task" has the meaning similar to the one of the business process [START_REF] Camarinha-Matos | Cloud-Based Collaborative Business Services Provision[END_REF], since the business process defines the way the "Service" is performed. "Task" has also a set of associated "Rules".

For the next stage, we are planning to elaborate in more details the willingness of devices to collaborate. The idea is that devices/assets have two operating modes -the so called "slave" mode, when the user/admin tells them what to do and the "free reasoning" mode when devices with the help of reasoning rules can discover the new assets and negotiate possible coalition formation. For the second case there is a need of ontologies that will define how the device/asset has to proceed to form a coalition. In the design mode, these ontologies can be updated or extended on demand.

Rule-based Reasoning

The reasoning component is the crucial part of the proposed solution. Reasoning mechanisms are responsible for many tasks, such as service discovery, service composition, and conflict resolution. To implement the reasoning part, a decision was made to use the Prolog engine as a powerful reasoning tool. Prolog is used through the PySWIP interface, enabling Prolog querying from within Python programs. Moreover, Python is used as a bridging point between the designer interface, Neo4j graph-oriented database and directly Prolog.

The rules can be used for addressing the reasoning challenges related to various CPS/IoT aspects. One example is the implementation of attribute-based access control (ABAC) model to manage the access in publish-subscribe networks based on MQTT [START_REF] Gabillon | Access Controls for IoT Networks[END_REF]. These authors also consider the conflict resolution policy relying on XACML standard that provides several possibilities for conflict resolution (deny overrides, permit overrides, etc.). The limitation of their approach is that the authors do not consider different user groups having different access rights. In [START_REF] Bohé | Towards low-effort development of advanced IoT applications[END_REF] the authors use basic Prolog rules to retrieve the sensor values or acquire data or conditions of the physical devices. The authors mention the conflict resolution module as a part of the future work. Different from the mentioned approaches, we specifically cover the issue of service composition trying to provide a high level technology-agnostic ecosystem for services management with conflict resolution mechanisms.

Concerning service composition, the rule-based approach is addressed in [START_REF] Thramboulidis | CPuS-IoT: A cyber-physical microservice and IoT-based framework for manufacturing assembly systems[END_REF] where the authors provide a framework for service composition in assembly systems. The core idea of the framework relies on the notion of microservice implying that a service is represented as a collection of sub-components called microservices. The authors consider that the IoT-compliant assembly workers exposing their properties as microservices. However, the proposed approach is not adapted to the automatic or semiautomatic service discovery and composition. In [START_REF] Xue | Manufacturing service composition method based on networked collaboration mode[END_REF] the authors allocate several stages of the service composition process, namely: (i) encapsulation of all resources as services, (ii) formulation or capture of the user demand, and (iii) bridging the customer demand with existing service or provide the optimal service composition.

The goal of the proposed design framework is to allow the designer not only to define the physical layout or structure of the system, but also to import and embed the corresponding reasoning mechanisms from the Knowledge Base to the design advisory or supervision component of the designed system. These reasoning mechanisms are delivered as functional ready-to-use blocks that will support the operational phase. One of these reasoning mechanisms is the service discovery, which serves the goal of bridging the user's demand and the proposition or suggesting a configuration for the service composition. The main idea here is to find the devices, e.g., sensors and/or actuators, that might satisfy the user needs that are formulated as user preferences. Below is a code snippet illustrating the discovery mechanisms: from pyswip import Prolog prolog = Prolog() prolog.assertz("sensor(sens_1, temperature, 20, room_1, john_smith)") prolog.assertz("sensor(sens_1, temperature, 20, room_1, john_smith)") prolog.assertz("sensor(sens_2, humidity, 50, room_1, jane_smith)") prolog.assertz("actuator(act_1, temperature, [increase, decrease, maintain], room_1, john_smith)") prolog.assertz("actuator(act_3, humidity, [increase, decrease, maintain], room_1, john_smith)") prolog.assertz("actuator(act_2, temperature, [increase, decrease, maintain], room_2, john_smith)") prolog.assertz("preference(john_smith, temperature, 20)") prolog.assertz("preference(john_smith, humidity, 50)") prolog.assertz("preference(jane_smith, temperature, 25)") prolog.assertz("user(john_smith, room_1)") prolog.assertz("user(jane_smith, room_1)") prolog.assertz("find_service(User, [Sensor, Actuator]) :-user(User, Smart_Environment),sensor(Sensor,Feature,_,Smart_Environment,_),actua tor(Actuator,Feature,_,Smart_Environment,_),preference(User,Feature,_ )") prolog.query("find_service(%s, [X,Y])") user = 'john_smith' seen = set() result = [] for soln in prolog.query("find_service(%s, [X,Y])" % (user)):

if soln not in result: result.append(soln)

By combining different reasoning mechanisms the designer can create a kind of a sequence that will be the part of the supervision component of the designed system. For instance, such sequence can have the following structure: firstly, discover devices with required capabilities secondly check the discovered devices for possible conflicts and then accomplish the service composition. In this way, during the system's development stage, the designer defines the structure and the order of capillary reasoning blocks execution through sequences establishment. For instance, the above-mentioned code allows the system to retrieve the sensors and actuators that are coping with the same attribute or parameter, are in the same location, and can satisfy the user need formulated within the Prolog fact "preference". It is worth mentioning, that a set of user`s preferences can be activated automatically. For instance, considering a Smart Home scenario, if a user enters a room, the temperature parameter can be automatically adjusted based on the "preference" field. This example serves the goal of demonstration that the system designer gets the discovery mechanism from the knowledge base without the need to additionally implement it. The discovery reasoning mechanism is part of another tool used to launch the negotiation process, if, for instance, the devices have different owners or are used by another user. After devices with required capabilities are discovered, conflict check mechanisms that need to find contradictions in users' needs and preferences that are in the same Smart Environment are launched.

For this purpose, we consider the following code as a part of a complex conflict check reasoning mechanism: check_task(Task, Bag) :task(Task,Sensor,_,_,Actuator,_,_,_,Location), findall(Name, (task(Name,Sensor,_,_,Actuator,_,_,_,Location), Name \= Task), Bag).

no_conflict(Task,H)

:-check_task(Task, Bag), member(H, Bag), task(H,_,_,Tar_Value,_,_,Tar_Action,_,_),task(Task,_,_,Ini_Value,_,_, Ini_Action,_,_), Ini_Value == Tar_Value, Ini_Action == Tar_Action.

The "Task" specifies the flow of actions required to provide a service addressing specific user need. In the case of composed service, the task has also the orchestration functions of different sub-services that are comprised in the composed service. Thus, the Task identifies the parameter/attribute that needs to be changed, as well as the required actuator action. As an example of actuator action -a thermostat example, which can increase the temperature, if it is lower than the one identified in the user preference, decrease if it is higher or maintain it, if it is around the preferred one. Thus, the first part of the code checks if there are tasks manipulating the same parameter and the second one defines the tasks that have no conflict. If the users have the same preferences there is no conflict, even if the users have different access rights and roles. The Figure 3 demonstrates the part of the prototype, namely the viewer displaying the structure of the composed services. The designer can establish a composed service through combination of different sub-services. The idea is that every composed service consists of a set of capillary services managing various attributes. In this example, the composed service "comfort_management" consists of the "temperature_regulation" and "humidity_regulation" sub-services. Every sub-services will subsequently have an attribute (humidity, temperature, etc.), which later, during the operation phase, will be connected with the real world devices delivering capabilities related to attribute. The proposed framework should assist the CCPS designer in building the system's structure and the logical core of the system. The logical core, in this context, contains a set of reasoning modules composed of reasoning rules. The framework enables the virtualization, i.e., abstraction from the low level, when the physical assets with corresponding functionality are managed as virtual entities (like digital twins). Contrary to some mentioned approaches, the proposed framework is intended to be technology agnostic, possessing some general reasoning modules that can be applied to various application domains. The next steps planned include the enriching of the reasoning core with further reasoning mechanisms and to consider the semi-automatic service composition during the operational phase. However, the focus is on the design phase and the tools that can be helpful for the CCPS designer to provide customized solutions.

Conclusion

This work is a logical continuation of previous works addressing some practical aspects of the Collaborative CPS design framework. The rising need to improve the digitalization of the complex systems affecting the digital transformation, forces to take the digitalization related challenges into consideration. In this regards, complex CPS composed of different heterogeneous constituents has to be designed in a certain way, when different mechanisms for services composition, conflict resolution, service discovery, etc., are stipulated. These reasoning mechanisms are the part of the supervision component of the designed system that will be executed during the operation phase. The designer is able to combine these mechanisms to develop a supervision component supporting the designed system. We provide some examples of the reasoning mechanisms devoted to service discovery and conflict check implemented in Prolog. These will be available for the designer from the Knowledge Base of the framework. Moreover, a collaborative service ontology is provided, indicating core concepts and their interrelations. Finally, the part of the CCPS design framework to construct the composed services was provided.

As a part of further work, we are developing rules for service composition that will include coalition formation and dissolution mechanisms, as well as introducing some domain-specific taxonomies that will be stored and available from Neo4j.

Fig. 1 .

 1 Fig. 1. Collaborative CPS design framework

Fig. 3 .

 3 Fig. 3. Composed service viewer

Acknowledgments. This work was supported in part by the Portuguese FCT foundation through the program UIDB/00066/2020.


Daniel Almeida
email: dg.almeida@campus.fct.unl.ptjcosta

João Costa

Alessandro Fantoni
email: afantoni@deetc.isel.ipl.ptmv@isel.ipl.pt

Manuela Vieira

Rib Waveguide Plasmonic Sensor for Lab-On-Chip Technology

Keywords: Plasmonics, Lab-on-chip, Amorphous silicon, Photonic integrated circuit

A prompt medical diagnosis is of major importance, starting the appropriate treatment earlier results in better outcomes and faster recovery times. Plasmonic biosensors based on photonic integrated circuits (PIC) are potential candidates in the development of lab-on-chip (LOC) technology, allowing digitalization of results and virtualization of laboratorial procedures in the detection of important biomarkers. These sensors have the advantages of high sensitivity and faster analysis when compared with traditional laboratorial methodologies. We study the possibility of exciting a surface plasmon, using low-cost fabrication methods and techniques based on amorphous silicon compounds, rib waveguide geometry and dimensions compatible with plasma-enhanced chemical vapor deposition (PECVD) and ultraviolet (UV) lithography. Results of Finite-Difference Time-Domain (FDTD) simulation of the plasmon excitation and sensor response are presented and discussed.

Introduction

Clinical assays are fundamental diagnostic tools employed to detect disease markers on samples of human tissue and fluids. Conventional techniques require expensive laboratory equipment and trained personnel, making the process complex, expensive and time-consuming. Lab-on-chip (LOC) technology, based on compact optical devices, such as photonic integrated circuit (PIC) biosensors, can be designed to detect several biomarkers (e.g. proteins, nucleic acids, drugs, pathogens and human cells) [START_REF] Kazanskiy | State-ofthe-art optical devices for biomedical sensing applications-a review[END_REF], paving the way to the development of Point-of-Care (PoC) diagnostic platforms. Studies demonstrate that these highly integrated sensors can be employed in the diagnosis of several diseases and health conditions, such as viruses [START_REF] Shrivastav | A comprehensive review on plasmonicbased biosensors used in viral diagnostics[END_REF], cancers [START_REF] Soler | Label-free nanoplasmonic sensing of tumor-associate autoantibodies for early diagnosis of colorectal cancer[END_REF] and acute kidney injury [START_REF] Albeltagy | Early diagnosis of acute kidney injury by urinary YKL-40 in critically ill patients in ICU: a pilot study[END_REF]. Early biomarker detection contributes to improving patient prognosis. State-of-the-Art photonic biosensors are able to detect analytes in a few minutes [START_REF] Soler | Label-free plasmonic biosensors for point-of-care diagnostics: a review[END_REF] and can achieve very high sensitivities [START_REF] Kazanskiy | State-ofthe-art optical devices for biomedical sensing applications-a review[END_REF], with detection limits between 10 -4 and 10 -6 RIU (refractive index units) or even less [START_REF] Kazanskiy | State-ofthe-art optical devices for biomedical sensing applications-a review[END_REF][START_REF] Soler | Principles, technologies, and applications of plasmonic biosensors[END_REF][START_REF] Diao | Diagnosis of acute respiratory syndrome coronavirus 2 infection by detection of nucleocapsid protein[END_REF][START_REF] Gauglitz | Critical assessment of relevant methods in the field of biosensors with direct optical detection based on fibers and waveguides using plasmonic, resonance, and interference effects[END_REF].

The success of PoC testing platforms is dependent on the development of technologies which are easily adapted to the detection of various analytes with high sensitivity and suitable for low-cost large scale deployment. Surface Plasmon Resonance sensors based on the Kretschmann configuration [START_REF] Kretschmann | Radiative decay of nonradiative surface plasmons excited by light[END_REF] are an example of a technology which excels on sensitivity and adaptability to different analytes. On the negative side, the equipment is too expensive and bulky for mass deployment in PoC applications. There is much interest in solutions that avoid large or expensive components, such as motor rotation stages and prisms, and which are based on low-cost materials and fabrication processes. In recent studies a large diversity of photonic sensor architectures comprising waveguides have been reported, the vast majority of sensors lay inside one of the following categories: 1) Plasmonic sensors based solely on waveguides [START_REF] Yuan | Design of a high-performance micro integrated surface plasmon resonance sensor based on silicon-on-insulator rib waveguide array[END_REF][START_REF] Jabbarzadeh | High performance dielectric loaded graphene plasmonic waveguide for refractive index sensing[END_REF][START_REF] Fantoni | Theory and FDTD simulations of an amorphous silicon planar waveguide structure suitable to be used as a surface plasmon resonance biosensor[END_REF]; 2) Interferometric sensors, Fig. 1, exploring surface plasmon resonance [START_REF] Da Lee | Mach-Zehnder interferometer refractive index sensor based on a plasmonic channel waveguide[END_REF][START_REF] Lotfi | High-sensitive plasmonic sensor based on Mach-Zehnder interferometer[END_REF][START_REF] Gupta | An optofluidic Young interferometer sensor for realtime imaging of refractive index in μTAS applications[END_REF], the evanescent wave effect [START_REF] Yuan | Mach-Zehnder interferometer biochemical sensor based on silicon-on-insulator rib waveguide with large cross section[END_REF] or the interference between two modes (bimodal waveguides) [START_REF] Jung | Modal analysis and design of silicon nitride rib waveguides for evanescent-wave bimodal biosensors[END_REF]; 3) Sensors employing one or more ring resonators [START_REF] Butt | Plasmonic refractive index sensor based on metal-insulator-metal waveguides with high sensitivity[END_REF][START_REF] Chou Chao | Highly sensitive metal-insulator-metal plasmonic refractive index sensor with a centrally coupled nanoring containing defects[END_REF], Fig. 1; 4) Sensors featuring cavities [START_REF] Rakhshani | High-Sensitivity Plasmonic Sensor Based on Metal-Insulator-Metal Waveguide and Hexagonal-Ring Cavity[END_REF][START_REF] Luo | A High Performance Plasmonic Sensor Based on Metal-Insulator-Metal Waveguide Coupled with a Double-Cavity Structure[END_REF]. The trend has been to reduce the form factor of the photonic circuits, to achieve higher integration, leveraged by sub-micrometer lithographic processes [START_REF] Chou Chao | Highly sensitive metal-insulator-metal plasmonic refractive index sensor with a centrally coupled nanoring containing defects[END_REF][START_REF] Luo | A High Performance Plasmonic Sensor Based on Metal-Insulator-Metal Waveguide Coupled with a Double-Cavity Structure[END_REF][START_REF] Rahmatiyar | Employment of cascaded coupled resonators for resolution enhancement in plasmonic refractive index sensors[END_REF][START_REF] Butt | Highly integrated plasmonic sensor design for the simultaneous detection of multiple analytes[END_REF][START_REF] Danaie | Design of a High-Resolution Metal-Insulator-Metal Plasmonic Refractive Index Sensor Based on a Ring-Shaped Si Resonator[END_REF], however, there is a major drawback in size reduction, which are the increased manufacturing costs. A possible alternative are larger photonic devices, which can be produced at lower costs [START_REF] Zilkie | Multi-micron silicon photonics platform for highly manufacturable and versatile photonic integrated circuits[END_REF]. Despite current trends, multi-micron sensor devices have been proposed in the last decade [START_REF] Yuan | Mach-Zehnder interferometer biochemical sensor based on silicon-on-insulator rib waveguide with large cross section[END_REF][START_REF] Jung | Modal analysis and design of silicon nitride rib waveguides for evanescent-wave bimodal biosensors[END_REF], these designs are based on rib waveguides. Considering the State-of-the-Art in biosensing, the following research question is proposed:

-What could be a suitable method to develop a low-cost, highly sensitive, compact and efficient sensor system that can be suitable to the detection of various biomarkers in point-of-care medical applications?

Sub-micron waveguides have the advantage of higher integration, however, when compared with multi-micron waveguides, the former have the disadvantages of higher losses and higher sensitivity to fabrication imperfections [START_REF] Zilkie | Multi-micron silicon photonics platform for highly manufacturable and versatile photonic integrated circuits[END_REF]. Multi-micron waveguides can be fabricated using low-cost processes with lower spatial resolutions, such as Plasma-Enhanced Chemical Vapor Deposition (PECVD) combined with ultraviolet (UV) lithography. Multi-micron rib waveguides have some advantages when compared with other waveguide types (e.g. strip waveguides), in terms of light coupling efficiency, losses and production costs, making them suitable for biosensing applications [START_REF] Yuan | Mach-Zehnder interferometer biochemical sensor based on silicon-on-insulator rib waveguide with large cross section[END_REF]. Large cross-section rib waveguides can be designed to support single-mode (SM) operation [START_REF] Soref | Large Single-Mode Rib Waveguides in GeSi-Si and Si-on-SiO2[END_REF][START_REF] Pogossian | The Single-Mode Condition for Semiconductor Rib Waveguides with Large Cross Section[END_REF][START_REF] Ziyang | Theoretical study of weakly-guided large-modearea rib waveguides: single-mode condition, birefringence, and supermode generation[END_REF], resulting in reduced light coupling loss when interfaced with optical fibers [START_REF] Solehmainen | Development of multi-step processing in silicon-on-insulator for optical waveguide applications[END_REF] and lower losses due to side-wall roughness [START_REF] Cassan | On-Chip Optical Interconnects With Compact and Low-Loss Light Distribution in Silicon-on-Insulator Rib Waveguides[END_REF]. Hydrogenated amorphous silicon (a-Si:H) and its compounds, hydrogenated amorphous silicon carbide (a-SiC:H) and hydrogenated amorphous silicon nitride (a-SiN:H), can be deposited by PECVD at lower temperatures (typically, between 200 °C -400 °C) [START_REF] Costa | Performance of an a-Si:H MMI multichannel beam splitter analyzed by computer simulation[END_REF], reducing fabrication costs. By controlling the compound percentages, it is possible to fine tune the material structure and optical properties, like for example the refractive index [START_REF] Vieira | SiC Multilayer Structures as Light Controlled Photonic Active Filters[END_REF], allowing the integration of several components, such as power splitters, interferometers, waveguides and photodetectors.

In this research, finite-difference time-domain (FDTD) and Finite Element Method (FEM) simulations are performed to study a SM rib waveguide surface plasmon resonance sensor. The photonic circuit is of low complexity and can be fabricated with inexpensive materials, such as silicon dioxide (SiO2) and nitrogen-rich a-SiN:H, the sensitive layer is made of a thin silver layer (Ag), with 40 nm thickness. The device can be fabricated using low-cost methods such as PECVD and UV lithography, also benefiting from better light coupling efficiency, due to its larger cross-section. The operating wavelength is 405 nm, the same used in high-definition optical discs, in the limit of the visible spectrum.

Contribution to Technological Innovation for Digitalization and Virtualization

Industry 4.0 is a concept devised to the industrial domain, comprising individualization and virtualization [START_REF] Chute | Introducing care 4.0: An integrated care paradigm built on industry 4.0 capabilities[END_REF], implemented by new technologies for automation and data exchange. This concept applied to the health domain is called Health 4.0 [START_REF] Thuemmler | Health 4.0: How virtualization and big data are revolutionizing healthcare. Heal. 4.0 How Virtualization Big Data are Revolutionizing Healthc[END_REF]. The six principles of Industry 4.0 [START_REF] Chute | Introducing care 4.0: An integrated care paradigm built on industry 4.0 capabilities[END_REF] are: 1) Interoperability; 2) Virtualization; 3) Decentralization; 4) Real-Time Capability; 5) Service Orientation; 6) Modularity. Biosensors and LOC technology contribute to all seven principles of Health 4.0:

Interoperability can be achieved by aggregation and integration of the different devices and services, being a major step towards the generation of meaningful information [START_REF] Thuemmler | Health 4.0: How virtualization and big data are revolutionizing healthcare. Heal. 4.0 How Virtualization Big Data are Revolutionizing Healthc[END_REF]. Data fusion combines information collected from different sensors to more accurately assess the patient's health conditions [START_REF] Haick | Artificial Intelligence in Medical Sensors for Clinical Decisions[END_REF], helping medical staff in the establishment of a personalized treatment.

With point-of-care analytical platforms, the clinical assay procedure can be partially virtualized, because the laboratory is "contained within a single device" and result interpretation can be made by computational algorithms, contributing to a significant reduction of the workload and the physical size of the lab.

Decentralization is accomplished due to the portability of the LOC platform, enabling clinical assays to be conducted in-loco, by a single doctor, nurse or analyst, the service is personalized, meaning healthcare can shift from centralized to a customized patient-oriented service.

Biosensors are extremely fast and typically can provide results within minutes [START_REF] Soler | Label-free plasmonic biosensors for point-of-care diagnostics: a review[END_REF], significantly contributing for real-time diagnosis. Due to the increased access to clinical assays, appropriate disease follow-up and prevention measures can be taken, so the probability of serious episodes and hospital admission lowers significantly.

The sensors' output is converted into the digital domain, allowing interfacing with latest generation networks (i.e. 5G) and cloud technologies, which are enablers for service orientation in the health domain [START_REF] Thuemmler | Health 4.0: How virtualization and big data are revolutionizing healthcare. Heal. 4.0 How Virtualization Big Data are Revolutionizing Healthc[END_REF]. The concept of modularity is also applicable to PoC equipment for medical assays, considering that the equipment features one or more receptacles were biosensor "cartridges" can be inserted or removed. Following this approach, LOCs can adapt to different analytes, the sensor "cartridges" can also be periodically upgraded or replaced if malfunctioning.

Another principle was added later: Safety, security and resilience [START_REF] Thuemmler | Health 4.0: How virtualization and big data are revolutionizing healthcare. Heal. 4.0 How Virtualization Big Data are Revolutionizing Healthc[END_REF]. In order to minimize the risks for the patients, it is important to assure the reliability and resilience of the system, by improving the biosensor's sensitivity and selectivity.

Conventional medical diagnostics rely primarily on the symptomatology, being prone to fail due to inadequate reporting or lack of symptoms on initial stages of disease [START_REF] Haick | Artificial Intelligence in Medical Sensors for Clinical Decisions[END_REF]. Machine learning (ML), artificial intelligence (AI) and the internet of things (IoT) have the potential to be applied with biosensors, allowing real-time monitoring [START_REF] Qazi | Smart biosensors for an efficient point of care (PoC) health management[END_REF].

Theoretical Background and Sensor Configuration

The sensor developed in this study is based on a SM silicon-on-insulator (SOI) rib waveguide, having an a-SiN:H core deposited over a SiO2 substrate, Fig. 2. The plasmonic section is covered by a thin silver (Ag) layer. It differs from the work of Fantoni et al. [START_REF] Fantoni | Theory and FDTD simulations of an amorphous silicon planar waveguide structure suitable to be used as a surface plasmon resonance biosensor[END_REF], because it is focused on a multi-micron design, made possible by a rib geometry, different waveguide materials and operating wavelength.

Single-Mode Rib Waveguide Dimensioning

It is desirable to design waveguides for SM propagation in order to maximize power efficiency. Rib waveguide SM operation was the focus of several studies [START_REF] Soref | Large Single-Mode Rib Waveguides in GeSi-Si and Si-on-SiO2[END_REF][START_REF] Pogossian | The Single-Mode Condition for Semiconductor Rib Waveguides with Large Cross Section[END_REF][START_REF] Ziyang | Theoretical study of weakly-guided large-modearea rib waveguides: single-mode condition, birefringence, and supermode generation[END_REF]. Rib waveguide geometry is characterized by three main parameters, rib width (w), rib height (H) and slab height (h), Fig. 2. To guarantee the design is compatible with low-cost lithographic and deposition processes (UV and PECVD), the width of the rib (w) should be equal to or greater than 1 μm, so it was set at 1.5 μm, to allow a small margin. Etch depth (D) was defined as 0.1 μm, the maximum r value was set at 0.9. Expression (1) establishes the relationship between rib waveguide design parameters and SM operation [START_REF] Pogossian | The Single-Mode Condition for Semiconductor Rib Waveguides with Large Cross Section[END_REF][START_REF] Ziyang | Theoretical study of weakly-guided large-modearea rib waveguides: single-mode condition, birefringence, and supermode generation[END_REF], the expression is valid for 0.5 ≤ r < 1. By replacing h in r = h/H by H -D, the rib height (H) can be obtained from ( 1):

w H ⁄ ≤ α + r • (1 -r 2 ) -1/2 . ( 1
)
Parameter α is 0 when considering the Effective Index Method (EIM), Pogossian et al. [START_REF] Pogossian | The Single-Mode Condition for Semiconductor Rib Waveguides with Large Cross Section[END_REF] or 0.3 according to Soref et al. [START_REF] Soref | Large Single-Mode Rib Waveguides in GeSi-Si and Si-on-SiO2[END_REF]. Following the more conservative approach of null α, the resulting rib height value is 0.82 μm, implying a slab height value of 0.72 μm, which were the dimensions used in this study.

Surface Plasmon Polariton (SPP) Excitation

Surface Plasmon Polaritons can only be excited by TM guided modes. In order to excite the SPP the effective refractive index difference between the plasmonic mode and the waveguide fundamental TM mode must be small. SPP complex refractive index as a function of angular frequency is given by (2):

n eff SPP (ω) = √ ε d (ω) ε m (ω) ε d (ω) + ε m (ω) , (2)
where ω is the angular frequency in rad/s, ε d (ω), ε m (ω) correspond to the complex permittivity function of the sample medium and metal, respectively. From (2) and considering that the effective refractive index of the waveguide's fundamental mode is similar to the index of the core material, the intersection point is found in Fig. 3. The resulting wavelength of 405.3 nm is ideal to excite the SPP from the fundamental TM mode of the waveguide. Results assume the sample medium is water, the metal layer is silver (refractive index from Jiang et al. [START_REF] Jiang | Realistic Silver Optical Constants for Plasmonics[END_REF]) and the waveguide material is a-SiN:H with Si/N ratio under 1 (refractive index from Charifi et al. [START_REF] Charifi | Opto-Structural Properties of Silicon Nitride Thin Films Deposited by ECR-PECVD[END_REF]). The intersection point occurs for a refractive index of 1.965.

Results

Modal Analysis

In Fig. 4, the major electric and magnetic XY field distributions are depicted, on the top of the rib a small field intensity is present, this effect makes plasmon excitation possible. The mode's effective refractive index is 1.949, the extinction coefficient is 2.8 × 10 -12 , because the material is considered non-dispersive. In Fig. 5, it is possible to notice the coupling between the fundamental TM mode of the rib waveguide and the surface plasmon mode, in this region of the sensor a thin silver layer with 40 nm thickness is deposited over the waveguide's core. The plasmonic field is visible over the center of the silver layer placed on top of the waveguide's rib. The effective refractive index of the mode is approximately 1.948. The deviation from the predicted refractive index of 1.965 (Fig. 3) is under 0.9 %.

In Fig. 6, the vertical cuts of the major electric and magnetic fields are represented, the higher peaks represent the waveguide fundamental TM mode, which is confined within the waveguide's core. Minor peaks are also visible, which correspond to the SPP propagating over the silver layer. The sensor's response was simulated for a waveguide length (LWG) of 12 μm and a silver layer length (LAg) of 10 μm, Fig. 2. FDTD simulations were performed for sample medium refractive index values between 1 and 1.52. The fundamental TM mode is coupled to the input of the waveguide and power is measured at the output.

In Fig. 7, for refractive index values between 1.29 and 1.31, a large dip is observable in the sensor's response, output power is under -2.7 dB, confirming the sensing behavior. The attenuation from the baseline is 2.2 dB.

Conclusions and Future Work

A plasmonic sensor based on a rib waveguide was designed and simulated. The waveguide geometry and multi-micron size allows light coupling from optical fibers, requiring only a plane-convex lens termination to converge the light beam. Due to the large size of the sensor, simple design and constituting materials (a-SiN:H), low-cost fabrication techniques can be employed, such as PECVD and UV lithography.

The sensitivity window covers the refractive index of human body fluids making it interesting to biosensing platforms. The dip in the power of the transfer function is still modest leaving room for improvement. Since the sensor operates with visible light (405nm), testing is facilitated. This wavelength is also used in high-definition optical disks. Further studies are necessary to establish the optimal metal and waveguide lengths. Equally important is the impact of the silicon-to-nitrogen ratio of a-SiN:H. Discovering the ideal proportion is fundamental to achieve the best plasmon excitation scenario. It is also necessary to improve the a-SiN:H model with k values based on experiments conducted at visible light wavelengths (400 nm to 700 nm).

Fig. 1 .

 1 Fig. 1. Top view of two photonic sensor configurations (simplified). (a) Mach-Zehnder Interferometer (MZI) implementation based on waveguides, comprising Y-junction splitter and combiner. (b) An example of ring resonator topology, the Vernier-cascade sensor [22], this configuration comprises three waveguides and two ring resonators, the filter ring resonator and input waveguide are totally covered by the cladding.

Fig. 2 .

 2 Fig. 2. Sensor design based on the rib waveguide. (a) Tridimensional model, LWG and LAg represent waveguide and silver layer lengths, respectively. (b) Transversal section, w represents rib width, H rib height and h slab height.

Fig. 3 .

 3 Fig. 3. Effective refractive index of the SPP (real component), represented in blue, refractive index of a-SiN:H with Si/N < 1 (real component), represented in red. The intersection point shows an ideal SPP excitation wavelength of 405 nm and a refractive index of 1.965.

Fig. 4 .

 4 Fig. 4. Fundamental TM mode of the rib waveguide obtained in FEM simulation. (a) Ey and (b) Hx fields. Layers are delimited by black lines (from top to bottom, water, a-SiN:H and SiO2).

Fig. 5 .

 5 Fig. 5. FEM simulation results of the coupling between the fundamental TM mode and the SPP. (a) Ey and (b) Hx fields. Layers are delimited by black lines (from top to bottom, water, silver, a-SiN:H and SiO2).

Fig. 6 .

 6 Fig. 6. Vertical cut of: (a) Ey and (b) Hx fields, the characteristic plasmon field profile is present on the top, showing coupling between the waveguide TM mode and SPP mode.

4. 2 Fig. 7 .

 27 Fig. 7. Transmitted power as a function of the sample medium refractive index.

D. Almeida et al.

Acknowledgments. Research supported by FCT -Fundação para a Ciência e Tecnologia, through grant SFRH/BD/07792/2021 and projects PTDC/NAN-OPT/31311/2017, FCT/MCTES: UIDB/00066/2020, and by Instituto Politécnico de Lisboa, through project IPL/2021/wavesensor_ISEL.


David Leonardo
email: d.leonardo@campus.fct.unl.pt

João Goes

An Energy-Efficient Wideband Input-Buffer for High-Speed CMOS ADCs

Keywords: ADC, Input Buffer, CMOS, High Linearity, High Bandwidth, Direct Conversion, Harmonic Distortion, Intermodulation Distortion

Input buffers (IBs) for driving analog-to-digital converters (ADCs) in direct down-conversion radio frontends are normally operated with supply voltages higher than the nominal, mainly due to bandwidth (BW) and dynamic linearity constraints. Therefore, several voltage-regulators are required as well as the need of having I/O devices capable of handling such voltages. An energyefficient input buffer architecture is presented in this paper and fairly compared to other existing IB realizations using a standard 1.2-V 130-nm CMOS technology as reference. The proposed new architecture presents better dynamic performance, and it can be readily used to drive moderate-resolution ADCs without requiring either a higher supply voltage or any non-standard I/O devices.

Introduction

Moderate resolution ADCs (10-to-12 bits) with sampling-rates of several GHz (1-to-8 GHz) and dissipating low power are in high demand for the next generation of communication systems. In fact, the input bandwidths (BW) requirements of the ADCs have continuously increased allowing down-convert signals directly from radiofrequency (RF) multi-GHz bands. This is a common practice to either reduce or eliminate the need for analog mixers and complex filters. For 5G receivers, for instance, ADCs with resolutions of 10-bit and sampling speeds in the range of 1-2 GHz are often employed [START_REF] Dermit | A 1.67-GSps TI 10-Bit Ping-Pong SAR ADC With 51-dB SNDR in 16-nm FinFET[END_REF].

With faster ADCs, these operations can move forward, into the digital domain, and carried out in software. Therefore, in modern radio-receiver systems, the ADC is closer to the antenna. As a result, the required input signal BW of the sample-and-hold (S/H) circuit in the frontend of the ADC cannot be directly and efficiently driven by the lownoise amplifier (LNA) without rising significantly the power dissipation of the whole receiving chain. Therefore, as it is shown in Fig. 1, a high-performance voltage inputbuffer (IB) should be added between the wideband LNA and the ADC to properly interface these two main building-blocks. Due to the fast sampling-rate (Fs) of the ADC a relatively short time (a few hundreds of picoseconds) is available for input signal tracking. During this window, the ADC driver must fully charge the large sampling capacitor with low noise and distortion.

In order to not degrade the overall dynamic performance of the entire receiving chain, the IB must reach excellent dynamic performance in terms of BW, linearity, and energy-efficiency. Consequently, the design of these (IBs) guarantee that the dynamic specifications of the ADC are not significantly degraded. Due to this reason, most of the existing solutions for these IBs require supply voltages higher than the nominal (core supply) values of the technology and, consequently, additional voltage regulators. In this paper, a novel wideband IB architecture is proposed. When compared with other existing solutions and using the same comparison conditions, our architecture presents an extended BW, better dynamic performance and higher energy-efficiency, and it can be readily used to drive moderate-resolution ADCs without requiring either a higher supply voltage or any non-standard I/O devices 2 State of the Art of Input Buffer Architectures 2.1 The Source-Follower (SF) and Cascade SF Due to its simplicity, the source-follower (SF), shown in Fig. 2(a), is the first design option for voltage buffers. The output voltage extracted on the source of a commondrain (CD) device (M1) is almost a perfect copy of its gate voltage if body-effect is eliminated [START_REF] Farag | High performance CMOS buffer amplifier with offset cancellation[END_REF]. Therefore, and despite the simplicity, the voltage buffer is an effective solution when nominal power-supply is not a major concern.

This design has, however, a few limitations that have been analyzed and optimized, over the years, in the literature. Limitations in the non-zero output resistance have been studied in [START_REF] Farag | High performance CMOS buffer amplifier with offset cancellation[END_REF][START_REF] Gray | Analysis and Design of Analog Integrated Circuits, 4th. Edition[END_REF][START_REF] Kong | An Ultra Low Output Resistance and Wide SwingVoltage Follower[END_REF]. Linearity issues with this design were studied in [START_REF] Rapakko | On the Performance and Use of an Improved Source-Follower Buffer[END_REF], as well as studies to overcome the level-shifting and offset at the output [START_REF] Gray | Analysis and Design of Analog Integrated Circuits, 4th. Edition[END_REF]. [START_REF] Xing | A Unity-Gain Buffer with Reduced Offset and Gain Error[END_REF]. This approach is used to keep the input common-mode voltage (VCMI) close to the output common-mode voltage (VCMO). In the design if VGS2 ≈ VSG1 then the VCMO ≈ VCMI. However, small changes in the process, voltage and temperature (PVT) of the operating design may incur in changes of VGS [START_REF] Xing | A Unity-Gain Buffer with Reduced Offset and Gain Error[END_REF].

Super Source-Follower (SSF)

Since most of the deep-submicron technologies operate with low positive power supply voltages ( 1.2 V) the simple SF and CSF voltage buffers may have a larger output resistance than the one needed to drive large capacitive loads [START_REF] Gray | Analysis and Design of Analog Integrated Circuits, 4th. Edition[END_REF][START_REF] Kong | An Ultra Low Output Resistance and Wide SwingVoltage Follower[END_REF]. Hence, in some cases, a super source-follower (SSF), as shown in Fig. 3, is used as an improved version of the traditional SF. In fact, this architecture can lower the output resistance of this buffer significantly, through the negative feedback implemented through commonsource (CS) transistor M2 [START_REF] Gray | Analysis and Design of Analog Integrated Circuits, 4th. Edition[END_REF][START_REF] Kong | An Ultra Low Output Resistance and Wide SwingVoltage Follower[END_REF]. However, due to the feedback in voltage-mode, it usually presents some bandwidth resonance in frequencies close to the cutoff frequency.

Nevertheless, this SSF buffer represents a significant improvement of the traditional SF, especially for heavy and switched capacitive loads, since it has a lower output resistance and the feedback loop on M2 corrects some of the non-linearity of the VGS signal dependency of CD device M1.

Current-Feedback Input Buffer (CFIB)

The current-feedback input buffer (CFIB), as shown in Fig. 4, differs from the SSF since its feedback is in current-mode rather than in voltage-mode. Similar to the SSF, this current-mode negative feedback also maximizes the dynamic linearity of the SF and CSF architectures [START_REF] Vaz | A 13b 4GS/s digitally assisted dynamic 3-stage asynchronous pipelined-SAR ADC[END_REF]. Moreover, it is better suited for operation with lower supply voltages.

The voltage at the drain of the main device M1 is used to regulate the VGS of device M2. This will regulate the current flowing on the common-gate device M2 that is mirrored and fed-back by the wide-swing dynamic cascode-current-mirror composed by M3A and M4A. This feedback is controlled by the current mirroring factor (e.g., 1 : K where K represents the mirroring-ratio and usually made equal to 2, 3 or 4) between devices M3A and M3B, and devices M4A and M4B.

To reach a larger and an almost flat BW, the parasitic capacitances in the currentmode feedback-loop (particularly at the gate terminals of mirroring devices M3A and M3B) need to be minimized and properly compensation. With proper compensation, the AC current required to charge these parasitic capacitors is kept at its minimum value [START_REF] Vaz | A 13b 4GS/s digitally assisted dynamic 3-stage asynchronous pipelined-SAR ADC[END_REF], while the feedback is still fast enough to improve (extend) the overall signal BW.

Cascade Source-Follower with VGS Control (CSF-VC)

Fig. 5 shows the basic concept of the CSF circuit with VGS control (CSF-VC) [START_REF] Xing | A Unity-Gain Buffer with Reduced Offset and Gain Error[END_REF]. A global negative-feedback loop in the CSF further reduces the output resistance and keeps VGS2≈VSG1, reducing both the constant and input-dependent components of the offset. Transistors M1 and M2 form the cascade source-follower. The gate and source of the PMOS transistor M3 are connected to the source and gate of NMOS device M2, allowing M3 to sense the VGS of M2. Transistors M1 and M3 form a differential pair with currentmirror load M4 and M5. If VGS2≠VSG1, the gate voltage of M9 is adjusted to change the current through M2 until VGS2 is approximately equal to VSG1. A major aspect of this circuit is that it uses, simultaneously, local negative-feedback and local feedforward in the source followers to set the gain almost equal to unity and global feedback, thus reducing the gain and offset errors. Since global feedback is applied to a circuit with a small gain error, the BW of the circuit is significantly increased compared to circuits relying on global feedback only to overcome gain errors. An additional compensation capacitor Cc needs to be added between the gate and the drain of transistor M9 for proper stabilization.

Proposed Input Buffer (IB) Circuit

The schematic of the proposed IB architecture is shown in Fig. 6. The main ideas behind our voltage buffer are: i) avoid the use of cascode structures at the output branch of the buffer circuit in order to maximize the output-swing and improve linearity; ii) implement all the necessary local feedback-loops, either positive or negative, in current-mode due to the reduced nominal power-supply. Common-drain (CD) devices M1 and M2 form a CSF and transistor M7 is in a common-gate (CG) configuration.

This IB uses two separated main current-mode feedback-loops. Similarly to the CFIB (removing the cascode device at the output branch), the first feedback-loop is implemented by the CG device M7 together with a wide-swing high-output impedance current-mirror comprising transistors M4 and M8-M11. When the voltage at the gate of M2 increases, the current increases. With this increase of the drain current, the voltage at the drain of M2 will decrease, decreasing the VGS of M7 (VCASP is a DC constant voltage biasing the CG device M7) and the current flowing through M7. The reduction in current in M7 will further decrease the gate voltage in M4. This first feedback-loop provides a local positive-feedback to guarantee additional bandwidth by quickly increase Vout when the input increases.

The second (negative) feedback-loop starts at the gate of M4, M9 and M14. When the voltage at this gate terminal decreases, then the current also decreases, since VGS is reduced. This will increase the drain voltage of M14, decreasing the drain current of M12 and M5 (M12 and M5 form a basic current-mirror) feeding the main CD input device M1. Using MATLAB TM tool for Symbolic Analysis of Analog Circuits the transfer function (TF) at low-frequencies, and tolerating an error of the order of 10 %, is given by:

) 5 1 ( m4 g ) 9 4 ( m1 g ) 9 4 ( m1 g Gain DC ds g ds g m g m g m g m g +  + +  +  = (1)
showing that the first stage feedback loop is the most important regarding low-frequency (DC) gain.

Simulation Results

The proposed IB has been designed and optimized employing a fully-differential structure and in a standard 1.2-V, 130-nm CMOS process node. Only standard devices have been employed. All IBs have been simulated in DC, AC, and using transient-noise simulations, in the same load conditions and with the same input signal (600 mVppdifferential). Hence, although the described IBs have different attenuations of the input signal at lower frequencies (DC gain), the output signal is kept similar for all topologies, in order to allow fair comparisons among all IBs. Moreover, all CD devices have been biased in the same operating bias condition in all the simulated IBs (i.e., in moderate inversion with VDSsat ~ 100 mV) and the (switched) capacitive load has been normalized to 1 pF. The frequency (AC) simulation results of the proposed IB demonstrate that the peaking at higher frequencies, which occurs in both circuits (SSF and the CFIB), is reduced in the proposed topology by employing the second current-mode negative feedback-loop. Fig. 6 shows the frequency response of each feedback-loop independently. Note that there are two resonances around the same frequency. Fig. 7 shows the overall (combined) simulated frequency response of the system where it is possible to see that the peaking is not that noticeable.

Transient-noise simulations have been performed in order to calculate the fast-Fourier-transform (FFT) of the output signal. The FFT results shown in Fig. 9 have been then used to calculate all key performance parameters regarding the dynamic linearity (THD and SFDR) and the signal-to-noise ratio (SNR). Similar simulations have been carried out of all the other IB architectures (also employing fully-differential designs), in order to compare them with the proposed IB. Table I shows the simulated key performance parameters for the different IBs.

In order to compare the energy-efficiency among the different IB solutions, and since the target application of the proposed IB is to drive high-speed ADCs, the well-known Walden figure-of-merit (FOM-W) has been used in the adapted form: . [START_REF] Farag | High performance CMOS buffer amplifier with offset cancellation[END_REF] to account for the dissipated power, the signal bandwidth (BW) and both, the noise and the dynamic linearity (the signal-to-noise-plus-distortion-ratio, SNDR, taking into consideration both, the total-harmonic-distortion, THD, and the simulated transient noise). In case of the FOM-W, the lower the number the better the efficiency of the IB.

As stated in the Introduction section, since the IB will be interfacing between the LNA and the ADC, it must reach excellent dynamic performance in terms of BW, linearity (SNDR), and energy-efficiency (Power). Consequently, the design of these (IBs) guarantee that the dynamic specifications and the key performance parameters of the ADC are not significantly degraded.

To the best of the authors knowledge, the proposed IB is, in simulation, the most energy-efficient IB (reaching 1.83 fJ) among all from prior art, supplied with a single and nominal power supply of 1.2 V and comprising only standard (core) devices. Notice that, although the proposed IB has the highest current consumption among all, since it uses more active branches, it achieves the highest effective bandwidth (2.2 GHz) and the best linearity without the need of any type of additional compensation.

Fig. 1 .

 1 Fig. 1. Direct-conversion receiver system.

Fig. 2 .

 2 Fig. 2. (a) Source-follower, SF; (b) Cascade source-follower, CSF.

Fig. 2 (

 2 Fig.2(b)shows the cascade source-follower (CSF) as early presented in[START_REF] Xing | A Unity-Gain Buffer with Reduced Offset and Gain Error[END_REF]. This approach is used to keep the input common-mode voltage (VCMI) close to the output common-mode voltage (VCMO). In the design if VGS2 ≈ VSG1 then the VCMO ≈ VCMI. However, small changes in the process, voltage and temperature (PVT) of the operating design may incur in changes of VGS[START_REF] Xing | A Unity-Gain Buffer with Reduced Offset and Gain Error[END_REF].

Fig. 3 .

 3 Fig. 3. Super source-follower (SSF).

Fig. 4 .

 4 Fig. 4. Current Feedback Input Buffer (CFIB).

Fig. 5 .

 5 Fig. 5. Cascade Source Follower with VGS sensing (CSF-VC).

Fig. 5 .

 5 Fig. 5. Proposed Input Buffer.

Fig. 6 .

 6 Fig. 6. Simulated frequency response of the two feedback-loops.

Fig. 7 .

 7 Fig. 7. Simulated frequency response of the proposed IB.

Fig. 8 .

 8 Fig. 8. Simulated FFT of the output signal (4096 bins and coherent sampling).

Table 1 .

 1 Simulation Results in 1.2-V 130-nm Standard CMOS.

		SF [2] CSF [8] CFIB [6] CSF-VC [8] Proposed IB
	Current consumption (mA) @ 1.2 V	2.0	2.6	3.0	2.8	5.5
	Bandwidth (GHz) @ CLOAD = 1pF	1.5	1.7	1.0	1.2	2.2
	Input signal frequency (MHz)	109	109	109	109	109

In order to compare the energy-efficiency among the different IB solutions, and since the target application of the proposed IB is to drive high-speed ADCs, the well-known Walden figure-of-merit (FOM-W) has been used in the adapted form: . [START_REF] Farag | High performance CMOS buffer amplifier with offset cancellation[END_REF] to account for the dissipated power, the signal bandwidth (BW) and both, the noise and the dynamic linearity (the signal-to-noise-plus-distortion-ratio, SNDR, taking into consideration both, the total-harmonic-distortion, THD, and the simulated transient noise). In case of the FOM-W, the lower the number the better the efficiency of the IB.

As stated in the Introduction section, since the IB will be interfacing between the LNA and the ADC, it must reach excellent dynamic performance in terms of BW, linearity (SNDR), and energy-efficiency (Power). Consequently, the design of these (IBs) guarantee that the dynamic specifications and the key performance parameters of the ADC are not significantly degraded.

To the best of the authors knowledge, the proposed IB is, in simulation, the most energy-efficient IB (reaching 1.83 fJ) among all from prior art, supplied with a single and nominal power supply of 1.2 V and comprising only standard (core) devices. Notice that, although the proposed IB has the highest current consumption among all, since it uses more active branches, it achieves the highest effective bandwidth (2.2 GHz) and the best linearity without the need of any type of additional compensation.

Conclusions

An energy-efficient input buffer architecture was presented in this paper and fairly compared to other existing IB realizations using a standard 1.2-V and 130-nm CMOS technology as reference. The proposed new architecture presents a better dynamic performance (fom, noise and distortion), it has a wider input signal BW and it can be readily used to drive moderate-resolution ADCs without requiring either a higher supply voltage or any non-standard I/O devices.