Optimal Cooperative MIMO Scheme in Wireless Sensor Networks

Cooperative Multiple-Input Multiple-Output (MIMO) has been proposed as a transmission strategy to combat the fading problem in Wireless Sensor Networks (WSNs) to reduce the retransmission probability and lower the transmission energy. Among the earliest work on cooperative MIMO in WSNs is the analysis of the Space-Time Block Coding (STBC) scheme to achieve lower Bit Error Rate (BER) and significant energy savings. The work is continued with the implementation of the Low-Energy Adaptive Clustering Hierarchy (LEACH) Medium Access Control (MAC) protocol for clustered-based architectures. The combination of STBC and the LEACH scheme resulted in a significant improvement in transmission energy efficiency compared to the Single-Input Single Output (SISO) scheme. Further study is conducted to compare the performance of STBC and various Spatial Multiplexing (SM) schemes such as Vertical Bell Labs Layered Space-Time (V-BLAST) and Diagonal BLAST. In this study, LEACH MAC was also utilized and lower transmission energy and latency were achieved against the SISO scheme. However, the centralized architecture leads to energy wastage and higher latency compared to a distributed architecture. On the other hand, the implementation of a distributed architecture needs to consider synchronisation issues. Thus a practical cooperative MIMO scheme for distributed asynchronous WSNs is needed. Moreover, a practical MAC that can suit cooperative transmission is required. A combination of a practical MAC protocol and an efficient MIMO scheme for asynchronous cooperative transmission leads to a more energy efficient and lower latency cooperative MIMO system. A combination of a MAC protocol and a cooperative SM scheme for cooperative MIMO transmission has been proposed in previous study where the combined scheme achieves significant energy efficiency and lower latency. Furthermore, a transmit Maximum Ratio Combiner (MRC) scheme is suggested to be more tolerant to the jitter difference than the Alamouti STC scheme in network with imperfect transmitting nodes synchronisation. In this chapter, we expand these studies to two other cooperative MIMO schemes, namely Beamforming (BF) and STBC for both network scenarios: perfect and imperfect transmitting nodes synchronisation. The optimal cooperative MIMO scheme combined with an appropriate MAC protocol should lead to the lowest energy consumption and lowest packet latency

A Non-Cooperative Game Theoretical Approach For Power Control In Virtual MIMO Wireless Sensor Network

Power management is one of the vital issue in wireless sensor networks, where the lifetime of the network relies on battery powered nodes. Transmitting at high power reduces the lifetime of both the nodes and the network. One efficient way of power management is to control the power at which the nodes transmit. In this paper, a virtual multiple input multiple output wireless sensor network (VMIMO-WSN)communication architecture is considered and the power control of sensor nodes based on the approach of game theory is formulated. The use of game theory has proliferated, with a broad range of applications in wireless sensor networking. Approaches from game theory can be used to optimize node level as well as network wide performance. The game here is categorized as an incomplete information game, in which the nodes do not have complete information about the strategies taken by other nodes. For virtual multiple input multiple output wireless sensor network architecture considered, the Nash equilibrium is used to decide the optimal power level at which a node needs to transmit, to maximize its utility. Outcome shows that the game theoretic approach considered for VMIMO-WSN architecture achieves the best utility, by consuming less power.Comment: 12 pages, 8 figure

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

Cooperative subcarrier sensing using antenna diversity based weighted virtual sub clustering

The idea of cooperation and the clustering amongst cognitive radios (CRs) has recently been focus of attention of research community, owing to its potential to improve performance of spectrum sensing (SS) schemes. This focus has led to the paradigm of cluster based cooperative spectrum sensing (CBCSS). In perspective of high date rate 4th generation wireless systems, which are characterized by orthogonal frequency division multiplexing (OFDM) and spatial diversity, there is a need to devise effective SS strategies. A novel CBCSS scheme is proposed for OFDM subcarrier detection in order to enable the non-contiguous OFDM (NC-OFDM) at the physical layer of CRs for efficient utilization of spectrum holes. Proposed scheme is based on the energy detection in MIMO CR network, using equal gain combiner as diversity combining technique, hard combining (AND, OR and Majority) rule as data fusion technique and antenna diversity based weighted clustering as virtual sub clustering algorithm. Results of proposed CBCSS are compared with conventional CBCSS scheme for AND, OR and Majority data fusion rules. Moreover the effects of antenna diversity, cooperation and cooperating clusters are also discussed

Energy-Efficient NOMA Enabled Heterogeneous Cloud Radio Access Networks

Heterogeneous cloud radio access networks (H-CRANs) are envisioned to be promising in the fifth generation (5G) wireless networks. H-CRANs enable users to enjoy diverse services with high energy efficiency, high spectral efficiency, and low-cost operation, which are achieved by using cloud computing and virtualization techniques. However, H-CRANs face many technical challenges due to massive user connectivity, increasingly severe spectrum scarcity and energy-constrained devices. These challenges may significantly decrease the quality of service of users if not properly tackled. Non-orthogonal multiple access (NOMA) schemes exploit non-orthogonal resources to provide services for multiple users and are receiving increasing attention for their potential of improving spectral and energy efficiency in 5G networks. In this article a framework for energy-efficient NOMA H-CRANs is presented. The enabling technologies for NOMA H-CRANs are surveyed. Challenges to implement these technologies and open issues are discussed. This article also presents the performance evaluation on energy efficiency of H-CRANs with NOMA.Comment: This work has been accepted by IEEE Network. Pages 18, Figure

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