ANFIS Based Data Rate Prediction For Cognitive Radio

Intelligence is needed to keep up with the rapid evolution of wireless communications, especially in terms of managing and allocating the scarce, radio spectrum in the highly varying and disparate modern environments. Cognitive radio systems promise to handle this situation by utilizing intelligent software packages that enrich their transceiver with radio-awareness, adaptability and capability to learn. A cognitive radio system participates in a continuous process, the ‘‘cognition cycle”, during which it adjusts its operating parameters, observes the results and, eventually takes actions, that is to say, decides to operate in a specific radio configuration (i.e., radio access technology, carrier frequency, modulation type, etc.) expecting to move the radio toward some optimized operational state. In such a process, learning mechanisms utilize information from measurements sensed from the environment, gathered experience and stored knowledge and guide in decision making. This thesis introduces and evaluates learning schemes that are based on adaptive neuro-fuzzy inference system (ANFIS) for predicting the capabilities (e.g. data rate) that can be achieved by a specific radio configuration in cognitive radio. First a ANFIS based scheme is proposed. The work reported here is compare previous neural network based learning schemes. Cognitive radio is a intelligent emergent technology, where learning schemes are needed to assist in its functioning. ANFIS based scheme is one of the good learning Artificial intelligence method, that combines best features of neural network and fuzzy logic. Here ANFIS and neural networks methods are able to assist a cognitive radio system to help in selecting the best one radio configuration to operate in. Performance metric like RMSE, prediction accuracy of ANFIS learning has been used as performance index

A Comprehensive Analysis of Literature Reported Mac and Phy Enhancements of Zigbee and its Alliances

Wireless communication is one of the most required technologies by the common man. The strength of this technology is rigorously progressing towards several novel directions in establishing personal wireless networks mounted over on low power consuming systems. The cutting-edge communication technologies like bluetooth, WIFI and ZigBee significantly play a prime role to cater the basic needs of any individual. ZigBee is one such evolutionary technology steadily getting its popularity in establishing personal wireless networks which is built on small and low-power digital radios. Zigbee defines the physical and MAC layers built on IEEE standard. This paper presents a comprehensive survey of literature reported MAC and PHY enhancements of ZigBee and its contemporary technologies with respect to performance, power consumption, scheduling, resource management and timing and address binding. The work also discusses on the areas of ZigBee MAC and PHY towards their design for specific applications

Survey of FPGA applications in the period 2000 – 2015 (Technical Report)

Romoth J, Porrmann M, Rückert U. Survey of FPGA applications in the period 2000 – 2015 (Technical Report).; 2017.Since their introduction, FPGAs can be seen in more and more different fields of applications. The key advantage is the combination of software-like flexibility with the performance otherwise common to hardware. Nevertheless, every application field introduces special requirements to the used computational architecture. This paper provides an overview of the different topics FPGAs have been used for in the last 15 years of research and why they have been chosen over other processing units like e.g. CPUs

Un cadre inter-couches pour la protection contre les interférences dans les réseaux ad-hoc radio cognitive

A fixed spectrum assignment scheme has a problem with resource deficiency in a wireless network. In 2002, the US Federal Communication Commission (FCC) reported that the radio spectrum was 20% to 85% under-utilized. The insufficient use of the spectrum is a critical issue for radio communication; as communication grows, a fixed spectrum becomes more limiting. The FCC then changed its spectrum management policy to make it more flexible by investigating the cognitive radio (CR) approach. Cognitive radio is a type of intelligent radio that explores the radio frequency environment, learns, and decides to use the unused portion of the frequency. The main functions of a CR are sensing, decision making, and sharing. However, these radios have to respect the standard wireless infrastructures by ensuring the least impact with their devices, also known as primary radios. Coexistence between CR systems and primary systems requires dedicated observation processes and interference management. In this thesis, observation from a CR point of view is presented. The overlapping area between a CR transmitter and primary radio (PR) transmitter is analysed so that it can be taken into account. The impact of this area is learnt by simulation and presented in Chapter 4. As a consequence, potential interference is envisaged. Along with observation, we investigate a proper mechanism to better prevent perturbation on PR devices using the Grey model and Kalman filter as a prediction model for predicting the density of primary receivers. In addition, we provide a strategy to combine the obtained observations into a metric that can be used in routing design in the context of coexistence between Cognitive Radio Networks (CRNs) and primary networks. The proposed strategy, using fuzzy logic, is presented in Chapter 5. In this chapter, we investigate how the routing layer reacts and makes the right decisions to maximise the spectrum resources, while avoiding interference with the primary receivers. For instance, a CR node can operate in an overlap region if primary receivers are inactive within this area. Also, we propose a routing mechanism based on the DYMO routing protocol that takes into account the observed relative impact. In the same chapter, we provide some practical scenarios illustrating the usefulness of our proposal. Interconnecting the CR nodes in CRNs is also a critical problem for the establishment of the network. We therefore present a beacon-based dissemination process in Chapter 6. In this chapter, we also describe a practical device designed for cognitive radio experiments. Even though our work affects different protocol layers, the designed framework is cross-layered. Indeed, the different components of the proposed framework access the various layers to retrieve information, process it, and react accordingly. Thus, our work constitutes a cross-layer framework for a local cognitive radio that aims to minimise the interference and maximise the network resources in cognitive radio networks.Le plan d’attribution du spectre présente un problème de déficit de ressources dans les réseaux sans fil. En 2002, la FCC (Federal Communication Commission) a rapporté que le spectre radioélectrique était de 20% à 85% sous-utilisé. L’utilisation inefficace du spectre est un problème majeur qui doit être résolu si l’on veut que les communications radio se développent. La FCC a ensuite changé la politique de gestion du spectre pour la rendre plus souple en s’interessant à l’approche radio cognitive (CR). La radio cognitive est un type de radio intelligente qui explore l’environnement de fréquences radio, apprend et décide d’utiliser la partie inutilisée du spectre. Les principales fonctions de la CR sont la détection, la prise de décision, et le partage. Cependant, ces radios doivent respecter les infrastructures sans fil standards en minimisant leur impact sur les appareils prioritaires, également appelés systèmes primaires. La coexistence entre les systèmes CR et les systèmes primaires nécessite des processus d’observation et de gestion des interférences dédiés. Dans cette thèse, nous nous sommes intéressés à la phase d’observation du point de vue CR. La zone de chevauchement entre un émetteur CR et l’émetteur primaire (PR) est analysée et prise en compte. L’impact de cette zone est appris par simulation et présenté dans le chapitre 4. En conséquence, des interférences potentielles sont envisagées. Durant la phase d’observation, nous étudions un mécanisme permettant de mieux prévenir la perturbation sur les dispositifs PR en utilisant le Grey Model et le filtre de Kalman comme modèle de prédiction de la densité des récepteurs primaires. En complément à cette observation, nous fournissons une stratégie visant à combiner les observations obtenues en une mesure qui pourra être utilisée par le routage dans le cadre de la coexistence entre réseaux radio cognitive (CRN) et réseaux primaires. La stratégie proposée utilise la logique floue et est présentée dans le chapitre 5. Dans ce chapitre, nous étudions comment la couche réseau réagit et prend les bonnes décisions pour maximiser l’utilisation des ressources du spectre, tout en évitant les interférences avec les récepteurs primaires. Par exemple, un noeud CR peut fonctionner dans une zone de recouvrement, si les récepteurs primaires sont inactifs dans cette zone. Ainsi, nous avons proposé un mécanisme de routage basé sur le protocole de routage DYMO qui prend en compte l’impact relatif observé. Dans ce même chapitre, nous avons également présenté des scénarios pratiques illustrant l’utilité de notre proposition. L’interconnexion des noeuds CR dans le CRN est aussi un problème crucial pour la mise en place du réseau. C’est pourquoi nous présentons un processus de diffusion par balises au chapitre 6. Dans ce chapitre, nous décrivons également un dispositif pratique conçu pour des expériences en radio cognitive. Même si notre travail se rapporte à différentes couches de la pile protocolaire, le cadre général que nous avons conçu est multicouches. En effet, les composants accèdent aux différentes couches pour récupérer l’information, la traiter et réagir en conséquence. Ainsi, notre travail constitue un environnement inter-couches pour un dispositif radio cognitive local visant à minimiser les interférences et à maximiser les ressources réseau dans les réseaux radio cognitive

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

Data Acquisition Applications

Data acquisition systems have numerous applications. This book has a total of 13 chapters and is divided into three sections: Industrial applications, Medical applications and Scientific experiments. The chapters are written by experts from around the world, while the targeted audience for this book includes professionals who are designers or researchers in the field of data acquisition systems. Faculty members and graduate students could also benefit from the book

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Cyber-Physical Embedded Systems with Transient Supervisory Command and Control: A Framework for Validating Safety Response in Automated Collision Avoidance Systems

The ability to design and engineer complex and dynamical Cyber-Physical Systems (CPS) requires a systematic view that requires a definition of level of automation intent for the system. Since CPS covers a diverse range of systemized implementations of smart and intelligent technologies networked within a system of systems (SoS), the terms “smart” and “intelligent” is frequently used in describing systems that perform complex operations with a reduced need of a human-agent. The difference between this research and most papers in publication on CPS is that most other research focuses on the performance of the CPS rather than on the correctness of its design. However, by using both human and machine agency at different levels of automation, or autonomy, the levels of automation have profound implications and affects to the reliability and safety of the CPS. The human-agent and the machine-agent are in a tidal lock of decision-making using both feedforward and feedback information flows in similar processes, where a transient shift within the level of automation when the CPS is operating can have undesired consequences. As CPS systems become more common, and higher levels of autonomy are embedded within them, the relationship between human-agent and machine-agent also becomes more complex, and the testing methodologies for verification and validation of performance and correctness also become more complex and less clear. A framework then is developed to help the practitioner to understand the difficulties and pitfalls of CPS designs and provides guidance to test engineering design of soft computational systems using combinations of modeling, simulation, and prototyping

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications