Energy-efficient Compressive Data Gathering Utilizing Virtual Multi-input Multi-output

Data gathering is an attractive operation for obtaining information in wireless sensor networks (WSNs). But one of important challenges is to minimize energy consumption of networks. In this paper, an integration of distributed compressive sensing (CS) and virtual multi-input multi-output (vMIMO) in WSNs is proposed to significantly decrease the data gathering cost. The scheme first constructs a distributed data compression model based on low density parity check-like (LDPC-like) codes. Then a cluster-based dynamic virtual MIMO transmission protocol is proposed. The number of clusters, number of cooperative nodes and the constellation size are determined by a new established optimization model under the restrictions of compression model. Finally, simulation results show that the scheme can reduce the data gathering cost and prolong the sensor network’s lifetime in a reliable guarantee of sensory data recovery quality

Power Optimisation and Relay Selection in Cooperative Wireless Communication Networks

Cooperative communications have emerged as a significant concept to improve reliability and throughput in wireless systems. In cooperative networks, the idea is to implement a scheme in wireless systems where the nodes can harmonize their resources thereby enhancing the network performance in different aspects such as latency, BER and throughput. As cooperation spans from the basic idea of transmit diversity achieved via MIMO techniques and the relay channel, it aims to reap somewhat multiple benefits of combating fading/burst errors, increasing throughput and reducing energy use. Another major benefit of cooperation in wireless networks is that since the concept only requires neighbouring nodes to act as virtual relay antennas, the concept evades the negative impacts of deployment costs of multiple physical antennas for network operators especially in areas where they are difficult to deploy. In cooperative communications energy efficiency and long network lifetimes are very important design issues, the focus in this work is on ad hoc and sensor network varieties where the nodes integrate sensing, processing and communication such that their cooperation capabilities are subject to power optimisation. As cooperation communications leads to trade-offs in Quality of Services and transmit power, the key design issue is power optimisation to dynamically combat channel fluctuations and achieve a net reduction of transmit power with the goal of saving battery life. Recent researches in cooperative communications focus on power optimisation achieved via power control at the PHY layer, and/or scheduling mechanism at the MAC layer. The approach for this work will be to review the power control strategy at the PHY layer, identify their associated trade-offs, and use this as a basis to propose a power control strategy that offers adaptability to channel conditions, the road to novelty in this work is a channel adaptable power control algorithm that jointly optimise power allocation, modulation strategy and relay selection. Thus, a novel relay selection method is developed and implemented to improve the performance of cooperative wireless networks in terms of energy consumption. The relay selection method revolves on selection the node with minimum distance to the source and destination. The design is valid to any wireless network setting especially Ad-hoc and sensor networks where space limitations preclude the implementation of bigger capacity battery. The thesis first investigates the design of relay selection schemes in cooperative networks and the associated protocols. Besides, modulation strategy and error correction code impact on energy consumption are investigated and the optimal solution is proposed and jointly implemented with the relay selection method. The proposed algorithm is extended to cooperative networks in which multiple nodes participate in cooperation in fixed and variable rate system. Thus, multi relay selection algorithm is proposed to improve virtual MIMO performance in terms of energy consumption. Furthermore, motivated by the trend of cell size optimisation in wireless networks, the proposed relay selection method is extended to clustered wireless networks, and jointly implemented with virtual clustering technique. The work will encompass three main stages: First, the cooperative system is designed and two major protocols Decode and Forward (DF) and amplify and forward (AF) are investigated. Second, the proposed algorithm is modelled and tested under different channel conditions with emphasis on its performance using different modulation strategies for different cooperative wireless networks. Finally, the performance of the proposed algorithm is illustrated and verified via computer simulations. Simulation results show that the distance based relay selection algorithm exhibits an improved performance in terms of energy consumption compared to the conventional cooperative schemes under different cooperative communication scenarios

A Survey of Low Duty Cycle MAC Protocols in Wireless Sensor Networks

22 page(s

Joint transceiver design and power optimization for wireless sensor networks in underground mines

Avec les grands développements des technologies de communication sans fil, les réseaux de capteurs sans fil (WSN) ont attiré beaucoup d’attention dans le monde entier au cours de la dernière décennie. Les réseaux de capteurs sans fil sont maintenant utilisés pour a surveillance sanitaire, la gestion des catastrophes, la défense, les télécommunications, etc. De tels réseaux sont utilisés dans de nombreuses applications industrielles et commerciales comme la surveillance des processus industriels et de l’environnement, etc. Un réseau WSN est une collection de transducteurs spécialisés connus sous le nom de noeuds de capteurs avec une liaison de communication distribuée de manière aléatoire dans tous les emplacements pour surveiller les paramètres. Chaque noeud de capteur est équipé d’un transducteur, d’un processeur de signal, d’une unité d’alimentation et d’un émetteur-récepteur. Les WSN sont maintenant largement utilisés dans l’industrie minière souterraine pour surveiller certains paramètres environnementaux, comme la quantité de gaz, d’eau, la température, l’humidité, le niveau d’oxygène, de poussière, etc. Dans le cas de la surveillance de l’environnement, un WSN peut être remplacé de manière équivalente par un réseau à relais à entrées et sorties multiples (MIMO). Les réseaux de relais multisauts ont attiré un intérêt de recherche important ces derniers temps grâce à leur capacité à augmenter la portée de la couverture. La liaison de communication réseau d’une source vers une destination est mise en oeuvre en utilisant un schéma d’amplification/transmission (AF) ou de décodage/transfert (DF). Le relais AF reçoit des informations du relais précédent et amplifie simplement le signal reçu, puis il le transmet au relais suivant. D’autre part, le relais DF décode d’abord le signal reçu, puis il le transmet au relais suivant au deuxième étage s’il peut parfaitement décoder le signal entrant. En raison de la simplicité analytique, dans cette thèse, nous considérons le schéma de relais AF et les résultats de ce travail peuvent également être développés pour le relais DF. La conception d’un émetteur/récepteur pour le relais MIMO multisauts est très difficile. Car à l’étape de relais L, il y a 2L canaux possibles. Donc, pour un réseau à grande échelle, il n’est pas économique d’envoyer un signal par tous les liens possibles. Au lieu de cela, nous pouvons trouver le meilleur chemin de la source à la destination qui donne le rapport signal sur bruit (SNR) de bout en bout le plus élevé. Nous pouvons minimiser la fonction objectif d’erreur quadratique moyenne (MSE) ou de taux d’erreur binaire (BER) en envoyant le signal utilisant le chemin sélectionné. L’ensemble de relais dans le chemin reste actif et le reste des relais s’éteint, ce qui permet d’économiser de l’énergie afin d’améliorer la durée de vie du réseau. Le meilleur chemin de transmission de signal a été étudié dans la littérature pour un relais MIMO à deux bonds mais est plus complexe pour un ...With the great developments in wireless communication technologies, Wireless Sensor Networks (WSNs) have gained attention worldwide in the past decade and are now being used in health monitoring, disaster management, defense, telecommunications, etc. Such networks are used in many industrial and consumer applications such as industrial process and environment monitoring, among others. A WSN network is a collection of specialized transducers known as sensor nodes with a communication link distributed randomly in any locations to monitor environmental parameters such as water level, and temperature. Each sensor node is equipped with a transducer, a signal processor, a power unit, and a transceiver. WSNs are now being widely used in the underground mining industry to monitor environmental parameters, including the amount of gas, water, temperature, humidity, oxygen level, dust, etc. The WSN for environment monitoring can be equivalently replaced by a multiple-input multiple-output (MIMO) relay network. Multi-hop relay networks have attracted significant research interest in recent years for their capability in increasing the coverage range. The network communication link from a source to a destination is implemented using the amplify-and-forward (AF) or decode-and-forward (DF) schemes. The AF relay receives information from the previous relay and simply amplifies the received signal and then forwards it to the next relay. On the other hand, the DF relay first decodes the received signal and then forwards it to the next relay in the second stage if it can perfectly decode the incoming signal. For analytical simplicity, in this thesis, we consider the AF relaying scheme and the results of this work can also be developed for the DF relay. The transceiver design for multi-hop MIMO relay is very challenging. This is because at the L-th relay stage, there are 2L possible channels. So, for a large scale network, it is not economical to send the signal through all possible links. Instead, we can find the best path from source-to-destination that gives the highest end-to-end signal-to-noise ratio (SNR). We can minimize the mean square error (MSE) or bit error rate (BER) objective function by sending the signal using the selected path. The set of relay in the path remains active and the rest of the relays are turned off which can save power to enhance network life-time. The best path signal transmission has been carried out in the literature for 2-hop MIMO relay and for multiple relaying it becomes very complex. In the first part of this thesis, we propose an optimal best path finding algorithm at perfect channel state information (CSI). We consider a parallel multi-hop multiple-input multiple-output (MIMO) AF relay system where a linear minimum mean-squared error (MMSE) receiver is used at the destination. We simplify the parallel network into equivalent series multi-hop MIMO relay link using best relaying, where the best relay ..

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology management is a crucial requirement, and in particular in massive scale deployments. Traditionally, clustering has been recognized as a common approach for topology management in ad-hoc networks, e.g., in Wireless Sensor Networks (WSNs). Topology management in WSNs and ad-hoc IoT networks has many design commonalities as both need to transfer data to the destination hop by hop. Thus, WSN clustering techniques can presumably be applied for topology management in ad-hoc IoT networks. This requires a comprehensive study on WSN clustering techniques and investigating their applicability to ad-hoc IoT networks. In this article, we conduct a survey of this field based on the objectives for clustering, such as reducing energy consumption and load balancing, as well as the network properties relevant for efficient clustering in IoT, such as network heterogeneity and mobility. Beyond that, we investigate the advantages and challenges of clustering when IoT is integrated with modern computing and communication technologies such as Blockchain, Fog/Edge computing, and 5G. This survey provides useful insights into research on IoT clustering, allows broader understanding of its design challenges for IoT networks, and sheds light on its future applications in modern technologies integrated with IoT.acceptedVersio

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Non-Metaheuristic Clustering Algorithms for Energy-Efficient Cooperative Communication in Wireless Sensor Networks: A Comparative Study

 Wireless Sensor Networks (WSNs) are now considered a vital technology that enables the gathering and distribution of data in various applications, such as environmental monitoring and industrial automation. Nevertheless, the finite energy resources of sensor nodes pose significant obstacles to the long-term viability and effectiveness of these networks. Researchers have developed and studied various non-meta algorithms to improve energy efficiency, data transfer, and network lifespan. These efforts contribute to enhancing cooperative communication modules. This analysis conducts a detailed examination and comparative evaluation of different well-known clustering methods in the field of Wireless Sensor Networks (WSNs), providing significant insights for improving cooperative communication. Our purpose is to provide a comprehensive perspective on the contributions of these algorithms to improving energy efficiency in WSNs. This will be achieved by examining their practical implementations, underlying mathematical principles, strengths, shortcomings, real-world applications, and potential for further improvement