| Wireless sensor networks (WSN) consist of numerous sensor nodes that are often deployed in harsh conditions and inaccessible places. The transmission reliability and link quality of WSN are generally dynamic and uncertain as a result of environmental interference and network dynamics. The communication capability of WSN can be limited by the nonlinear disturbances and stochastic perturbations of the network system. Moreover, limited energy is also a key factor to ensuring the quality of service of the network given battery-powered sensor nodes. The existing algorithms for power control in WSN with high-energy consumption are unaware of the network dynamics and lead to non-adaptive patterns. Thus, a multivariable fuzzy algorithm for power control and a dynamic adaptive fuzzy algorithm for power control (DAFPC) in WSN are proposed in this paper, which are based on the fuzzy control theory and the input-output-feedback mechanism. The main contributions of this study are as follows:Firstly, the research status, existing problems and techniques related to power control and transmission reliability in WSN are presented in detail. Then, the key parameters of link quality are provided following the correlation analysis of the link quality indicator (LQI), received signal strength indicator (RSSI) and packet reception ratio (PRR). The peer-to-peer, multiple nodes and energy consumption models of WSN are also presented.Secondly, a multivariable fuzzy algorithm for power control and a DAFPC algorithm in WSN are proposed in this paper, as mentioned previously. Fuzzy control theory and the input-output-feedback mechanism are applied in these algorithms. The stability of the closed-loop system in DAFPC is analyzed as well. In DAFPC, the controller parameter and the transmission power of the nodes are adaptively adjusted according to the link quality. Thus, the anti-interference capability is effectively improved.Lastly, simulation experiments are conducted on common power (COMPOW), non-adaptive fuzzy power control, multivariable fuzzy power control, and the DAFPC algorithm. Simulation results show that DAFPC can adapt to the dynamic changes in the network, effectively enhance the anti-interference performance and transmission reliability of WSN, reduce the energy consumption of the nodes and prolong network lifetime. |
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