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Consejo Nacional de Ciencia y Tecnología, CONACYT: 236188
Generically Dependent Continuant
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Distributed power control in mobile wireless sensor networks
Controlling the transmission power level in a mobile wireless sensor network is an essential process to improve the energy efficiency and quality of service (QoS) at each wireless node. To achieve this goal, we propose to evaluate the QoS by an estimation of the signal-to-interference noise ratio (SINR) according to the IEEE 802.15.4 standard. For this purpose, the received signal strength indicator per packet (RSSIp), and general received signal strength indicator (RSSIg) metrics are considered in this research work followed by a filtering stage to reduce the variability in the SINR estimation. In addition, this research work aims to evaluate different dynamic power control algorithms through an experimental test-bed, where the wireless nodes are in motion. A comparative analysis is presented of five distributed power control algorithms: fixed-step, Foschini-Miljanic, proportional-integral-derivative control, variable structure control, and water-filling control. Moreover, a new distributed power control technique is proposed for mobile wireless sensor networks: modified fixed-step (MFS). All the power allocation algorithms use the tracking error between the estimated and objective SINRs as the driving mechanism to adjust the transmission power. In general, the results show that a dynamic power allocation scheme not only enables the efficient use of the battery, extending its lifetime, but also it is able to achieve the desired QoS despite multiple interference and mobility of the nodes in the network. Furthermore, the results of the experimental evaluation indicate that the modified fixed-step algorithm has the best performance as a function of the reference tracking of the QoS and power consumption. © 2018 Elsevier B.V.
Energy efficiency; Mobile wireless sensor network; Power control; Quality of service Energy efficiency; IEEE Standards; Power control; Proportional control systems; Quality of service; Sensor nodes; Signal analysis; Signal interference; Signal to noise ratio; Two term control systems; Variable structure control; Distributed power control; Distributed power control algorithms; Mobile wireless sensor network; Power allocation algorithms; Proportional integral derivative control; Received signal strength indicators; Signal to interference-noise ratios; Transmission power levels; Quality control
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