925 research outputs found

    Lifetime Improvement in Wireless Sensor Networks via Collaborative Beamforming and Cooperative Transmission

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    Collaborative beamforming (CB) and cooperative transmission (CT) have recently emerged as communication techniques that can make effective use of collaborative/cooperative nodes to create a virtual multiple-input/multiple-output (MIMO) system. Extending the lifetime of networks composed of battery-operated nodes is a key issue in the design and operation of wireless sensor networks. This paper considers the effects on network lifetime of allowing closely located nodes to use CB/CT to reduce the load or even to avoid packet-forwarding requests to nodes that have critical battery life. First, the effectiveness of CB/CT in improving the signal strength at a faraway destination using energy in nearby nodes is studied. Then, the performance improvement obtained by this technique is analyzed for a special 2D disk case. Further, for general networks in which information-generation rates are fixed, a new routing problem is formulated as a linear programming problem, while for other general networks, the cost for routing is dynamically adjusted according to the amount of energy remaining and the effectiveness of CB/CT. From the analysis and the simulation results, it is seen that the proposed method can reduce the payloads of energy-depleting nodes by about 90% in the special case network considered and improve the lifetimes of general networks by about 10%, compared with existing techniques.Comment: Invited paper to appear in the IEE Proceedings: Microwaves, Antennas and Propagation, Special Issue on Antenna Systems and Propagation for Future Wireless Communication

    Efficient calculation of sensor utility and sensor removal in wireless sensor networks for adaptive signal estimation and beamforming

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    Wireless sensor networks are often deployed over a large area of interest and therefore the quality of the sensor signals may vary significantly across the different sensors. In this case, it is useful to have a measure for the importance or the so-called "utility" of each sensor, e.g., for sensor subset selection, resource allocation or topology selection. In this paper, we consider the efficient calculation of sensor utility measures for four different signal estimation or beamforming algorithms in an adaptive context. We use the definition of sensor utility as the increase in cost (e.g., mean-squared error) when the sensor is removed from the estimation procedure. Since each possible sensor removal corresponds to a new estimation problem (involving less sensors), calculating the sensor utilities would require a continuous updating of different signal estimators (where is the number of sensors), increasing computational complexity and memory usage by a factor. However, we derive formulas to efficiently calculate all sensor utilities with hardly any increase in memory usage and computational complexity compared to the signal estimation algorithm already in place. When applied in adaptive signal estimation algorithms, this allows for on-line tracking of all the sensor utilities at almost no additional cost. Furthermore, we derive efficient formulas for sensor removal, i.e., for updating the signal estimator coefficients when a sensor is removed, e.g., due to a failure in the wireless link or when its utility is too low. We provide a complexity evaluation of the derived formulas, and demonstrate the significant reduction in computational complexity compared to straightforward implementations

    Cooperative beamsteering in wireless sensor network based on backtracking search algorithm

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    The progressive development of Wireless Sensor Network (WSNs) contributes to many applications such as in the intelligent transport system (ITS), safety monitoring, military and in natural disasters prevention. In parallel to WSNs, the idea of internet of things (IoT) is developed where IoT can be defined as an interconnection between identifiable devices within the internet connection in sensing and monitoring processes. With recent growth in both size and power efficient computing, the concept of the ubiquitous WSN has aggressively emerged as an acknowledged research topic. As the capabilities of individual nodes in WSNs increase, so does the opportunity to perform more complicated tasks, such as cooperative beamsteering (CB). This CB manages to improve the range of communications and save precious battery power during the transmission. Therefore, this research proposes a meta-heuristic algorithm to organize node location in array arrangement. It is expected to effectively improve radiation beampattern fluctuations, exhibits lower complexity and less energy. From the simulation that has been done, it's observed that the proposed algorithm helps to reduce the side lobe level, thus better radiation beampattern is achieved

    Optimisation of Mobile Communication Networks - OMCO NET

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    The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

    Backtracking Search Optimization for Collaborative Beamforming in Wireless Sensor Networks

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    Due to energy limitation and constraint in communication capabilities, the undesirable high battery power consumption has become one of the major issues in wireless sensor network (WSN). Therefore, a collaborative beamforming (CB) method was introduced with the aim to improve the radiation beampattern in order to compensate the power consumption. A CB is a technique which can increase the sensor node gain and performance by aiming at the desired objectives through intelligent capabilities. The sensor nodes were located randomly in WSN environment. The nodes were designed to cooperate among each other and act as a collaborative antenna array. The configuration of the collaborative nodes was modeled in circular array formation. The position of array nodes was determined by obtaining the optimum parameters pertaining to the antenna array which implemented by using Backtracking Search Optimization Algorithm (BSA). The parameter considered in the project was the side-lobe level minimization. It was observed that, the suppression of side-lobe level for BSA was better compared to the radiation beampattern obtained for conventional uniform circular array

    Wireless Power Transfer and Data Collection in Wireless Sensor Networks

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    In a rechargeable wireless sensor network, the data packets are generated by sensor nodes at a specific data rate, and transmitted to a base station. Moreover, the base station transfers power to the nodes by using Wireless Power Transfer (WPT) to extend their battery life. However, inadequately scheduling WPT and data collection causes some of the nodes to drain their battery and have their data buffer overflow, while the other nodes waste their harvested energy, which is more than they need to transmit their packets. In this paper, we investigate a novel optimal scheduling strategy, called EHMDP, aiming to minimize data packet loss from a network of sensor nodes in terms of the nodes' energy consumption and data queue state information. The scheduling problem is first formulated by a centralized MDP model, assuming that the complete states of each node are well known by the base station. This presents the upper bound of the data that can be collected in a rechargeable wireless sensor network. Next, we relax the assumption of the availability of full state information so that the data transmission and WPT can be semi-decentralized. The simulation results show that, in terms of network throughput and packet loss rate, the proposed algorithm significantly improves the network performance.Comment: 30 pages, 8 figures, accepted to IEEE Transactions on Vehicular Technolog

    Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey

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    This paper provides a comprehensive review of the domain of physical layer security in multiuser wireless networks. The essential premise of physical-layer security is to enable the exchange of confidential messages over a wireless medium in the presence of unauthorized eavesdroppers without relying on higher-layer encryption. This can be achieved primarily in two ways: without the need for a secret key by intelligently designing transmit coding strategies, or by exploiting the wireless communication medium to develop secret keys over public channels. The survey begins with an overview of the foundations dating back to the pioneering work of Shannon and Wyner on information-theoretic security. We then describe the evolution of secure transmission strategies from point-to-point channels to multiple-antenna systems, followed by generalizations to multiuser broadcast, multiple-access, interference, and relay networks. Secret-key generation and establishment protocols based on physical layer mechanisms are subsequently covered. Approaches for secrecy based on channel coding design are then examined, along with a description of inter-disciplinary approaches based on game theory and stochastic geometry. The associated problem of physical-layer message authentication is also introduced briefly. The survey concludes with observations on potential research directions in this area.Comment: 23 pages, 10 figures, 303 refs. arXiv admin note: text overlap with arXiv:1303.1609 by other authors. IEEE Communications Surveys and Tutorials, 201
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