Spatial correlation based low energy aware clustering (LEACH) in a wireless sensor networks

In this paper, an enhanced Low Energy Aware Cluster Head (LEACH) protocol is proposed. It applies aggregation strategies in the area monitored by sensor nodes to reduce the number of reports sent to sink and to save energy. The basic idea is to weight the information sensed by sensors based on the distortion area in order to estimate better the event at the sink node. This approach seeks to exploit the spatial correlation among nodes and among clusters to assign different importance to the information aggregated and forwarded by the cluster head nodes. A multi-zone monitoring related to clusters is proposed, and a dynamic weights management is presented to consider distortion at cluster level introduced in the event estimation. A mathematical formulation of the problem and the proposal to weight space and data information is led out. Simulation campaigns in Matlab show the effectiveness of the event estimation in terms of event estimation distortion and network lifetime

Task-Oriented Over-the-Air Computation for Multi-Device Edge AI

Departing from the classic paradigm of data-centric designs, the 6G networks for supporting edge AI features task-oriented techniques that focus on effective and efficient execution of AI task. Targeting end-to-end system performance, such techniques are sophisticated as they aim to seamlessly integrate sensing (data acquisition), communication (data transmission), and computation (data processing). Aligned with the paradigm shift, a task-oriented over-the-air computation (AirComp) scheme is proposed in this paper for multi-device split-inference system. In the considered system, local feature vectors, which are extracted from the real-time noisy sensory data on devices, are aggregated over-the-air by exploiting the waveform superposition in a multiuser channel. Then the aggregated features as received at a server are fed into an inference model with the result used for decision making or control of actuators. To design inference-oriented AirComp, the transmit precoders at edge devices and receive beamforming at edge server are jointly optimized to rein in the aggregation error and maximize the inference accuracy. The problem is made tractable by measuring the inference accuracy using a surrogate metric called discriminant gain, which measures the discernibility of two object classes in the application of object/event classification. It is discovered that the conventional AirComp beamforming design for minimizing the mean square error in generic AirComp with respect to the noiseless case may not lead to the optimal classification accuracy. The reason is due to the overlooking of the fact that feature dimensions have different sensitivity towards aggregation errors and are thus of different importance levels for classification. This issue is addressed in this work via a new task-oriented AirComp scheme designed by directly maximizing the derived discriminant gain

New Coding/Decoding Techniques for Wireless Communication Systems

Wireless communication encompasses cellular telephony systems (mobile communication), wireless sensor networks, satellite communication systems and many other applications. Studies relevant to wireless communication deal with maintaining reliable and efficient exchange of information between the transmitter and receiver over a wireless channel. The most practical approach to facilitate reliable communication is using channel coding. In this dissertation we propose novel coding and decoding approaches for practical wireless systems. These approaches include variable-rate convolutional encoder, modified turbo decoder for local content in Single-Frequency Networks, and blind encoder parameter estimation for turbo codes. On the other hand, energy efficiency is major performance issue in wireless sensor networks. In this dissertation, we propose a novel hexagonal-tessellation based clustering and cluster-head selection scheme to maximize the lifetime of a wireless sensor network. For each proposed approach, the system performance evaluation is also provided. In this dissertation the reliability performance is expressed in terms of bit-error-rate (BER), and the energy efficiency is expressed in terms of network lifetime

Data fusion of multi-sensor for IOT precise measurement based on improved PSO algorithms

AbstractThis work proposes an improved particle swarm optimization (PSO) method to increase the measurement precision of multi-sensors data fusion in the Internet of Things (IOT) system. Critical IOT technologies consist of a wireless sensor network, RFID, various sensors and an embedded system. For multi-sensor data fusion computing systems, data aggregation is a main concern and can be formulated as a multiple dimensional based on particle swarm optimization approaches. The proposed improved PSO method can locate the minimizing solution to the objective cost function in multiple dimensional assignment themes, which are considered in particle swarm initiation, cross rules and mutation rules. The optimum seclusion can be searched for efficiently with respect to reducing the search range through validated candidate measures. Experimental results demonstrate that the proposed improved PSO method for multi-sensor data fusion is highly feasible for IOT system applications

Program of the 3rd International Conference on Signal Processing and Communication Systems, Omaha, Nebraska, 28-30 September 2009

10 sessions; 2 poster sessions. Schedule and Table of Contents

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

Energy-driven techniques for massive machine-type communications

In the last few years, a lot of effort has been put into the development of the fifth generation of cellular networks (5G). Given the vast heterogeneity of devices coexisting in these networks, new approaches have been sought to meet all requirements (e.g., data rate, coverage, delay, etc.). Within that framework, massive machine-type communications (mMTC) emerge as a promising candidate to enable many Internet of Things applications. mMTC define a type of systems where large sets of simple and battery-constrained devices transmit short data packets simultaneously. Unlike other 5G use cases, in mMTC, a low cost and power consumption are extensively pursued. Due to these specifications, typical humantype communications (HTC) solutions fail in providing a good service. In this dissertation, we focus on the design of energy-driven techniques for extending the lifetime of mMTC terminals. Both uplink (UL) and downlink (DL) stages are addressed, with special attention to the traffic models and spatial distribution of the devices. More specifically, we analyze a setup where groups of randomly deployed sensors send their (possibly correlated) observations to a collector node using different multiple access schemes. Depending on their activity, information might be transmitted either on a regular or sporadic basis. In that sense, we explore resource allocation, data compression, and device selection strategies to reduce the energy consumption in the UL. To further improve the system performance, we also study medium access control protocols and interference management techniques that take into account the large connectivity in these networks. On the contrary, in the DL, we concentrate on the support of wireless powered networks through different types of energy supply mechanisms, for which proper transmission schemes are derived. Additionally, for a better representation of current 5G deployments, the presence of HTC terminals is also included. Finally, to evaluate our proposals, we present several numerical simulations following standard guidelines. In line with that, we also compare our approaches with state-of-the-art solutions. Overall, results show that the power consumption in the UL can be reduced with still good performance and that the battery lifetimes can be improved thanks to the DL strategies.En els últims anys, s'han dedicat molts esforços al desenvolupament de la cinquena generació de telefonia mòbil (5G). Donada la gran heterogeneïtat de dispositius coexistint en aquestes xarxes, s'han buscat nous mètodes per satisfer tots els requisits (velocitat de dades, cobertura, retard, etc.). En aquest marc, les massive machine-type communications (mMTC) sorgeixen com a candidates prometedores per fer possible moltes aplicacions del Internet of Things. Les mMTC defineixen un tipus de sistemes en els quals grans conjunts de dispositius senzills i amb poca bateria, transmeten simultàniament paquets de dades curts. A diferència d'altres casos d'ús del 5G, en mMTC es persegueix un cost i un consum d'energia baixos. A causa d'aquestes especificacions, les solucions típiques de les human-type communications (HTC) no aconsegueixen proporcionar un bon servei. En aquesta tesi, ens centrem en el disseny de tècniques basades en l'energia per allargar la vida útil dels terminals mMTC. S'aborden tant les etapes del uplink (UL) com les del downlink (DL), amb especial atenció als models de trànsit i a la distribució espacial dels dispositius. Més concretament, analitzem un escenari en el qual grups de sensors desplegats aleatòriament, envien les seves observacions (possiblement correlades) a un node col·lector utilitzant diferents esquemes d'accés múltiple. Depenent de la seva activitat, la informació es pot transmetre de manera regular o esporàdica. En aquest sentit, explorem estratègies d'assignació de recursos, compressió de dades, i selecció de dispositius per reduir el consum d'energia en el UL. Per millorar encara més el rendiment del sistema, també estudiem protocols de control d'accés al medi i tècniques de gestió d'interferències que tinguin en compte la gran connectivitat d'aquestes xarxes. Per contra, en el DL, ens centrem en el suport de les wireless powered networks mitjançant diferents mecanismes de subministrament d'energia, per als quals es deriven esquemes de transmissió adequats. A més, per una millor representació dels desplegaments 5G actuals, també s'inclou la presència de terminals HTC. Finalment, per avaluar les nostres propostes, presentem diverses simulacions numèriques seguint pautes estandarditzades. En aquesta línia, també comparem els nostres enfocaments amb les solucions de l'estat de l'art. En general, els resultats mostren que el consum d'energia en el UL pot reduir-se amb un bon rendiment i que la durada de la bateria pot millorar-se gràcies a les estratègies del DL.En los últimos años, se han dedicado muchos esfuerzos al desarrollo de la quinta generación de telefonía móvil (5G). Dada la gran heterogeneidad de dispositivos coexistiendo en estas redes, se han buscado nuevos métodos para satisfacer todos los requisitos (velocidad de datos, cobertura, retardo, etc.). En este marco, las massive machine-type communications (mMTC) surgen como candidatas prometedoras para hacer posible muchas aplicaciones del Internet of Things. Las mMTC definen un tipo de sistemas en los cuales grandes conjuntos de dispositivos sencillos y con poca batería, transmiten simultáneamente paquetes de datos cortos. A diferencia de otros casos de uso del 5G, en mMTC se persigue un coste y un consumo de energía bajos. A causa de estas especificaciones, las soluciones típicas de las human-type communications (HTC) no consiguen proporcionar un buen servicio. En esta tesis, nos centramos en el diseño de técnicas basadas en la energía para alargar la vida ´útil de los terminales mMTC. Se abordan tanto las etapas del uplink (UL) como las del downlink (DL), con especial atención a los modelos de tráfico y a la distribución espacial de los dispositivos. Más concretamente, analizamos un escenario en el cual grupos de sensores desplegados aleatoriamente, envían sus observaciones (posiblemente correladas) a un nodo colector utilizando diferentes esquemas de acceso múltiple. Dependiendo de su actividad, la información se puede transmitir de manera regular o esporádica. En este sentido, exploramos estrategias de asignación de recursos, compresión de datos, y selección de dispositivos para reducir el consumo de energía en el UL. Para mejorar todavía más el rendimiento del sistema, también estudiamos protocolos de control de acceso al medio y técnicas de gestión de interferencias que tengan en cuenta la gran conectividad de estas redes. Por el contrario, en el DL, nos centramos en el soporte de las wireless powered networks mediante diferentes mecanismos de suministro de energía, para los cuales se derivan esquemas de transmisión adecuados. Además, para una mejor representación de los despliegues 5G actuales, también se incluye la presencia de terminales HTC. Finalmente, para evaluar nuestras propuestas, presentamos varias simulaciones numéricas siguiendo pautas estandarizadas. En esta línea, también comparamos nuestros enfoques con las soluciones del estado del arte. En general, los resultados muestran que el consumo de energía en el UL puede reducirse con un buen rendimiento y que la duración de la batería puede mejorarse gracias a las estrategias del DLPostprint (published version