Distributed Beampattern Optimization of Collaborative Beamforming for Wireless Sensor Networks

The optimization problem of sidelobe control for Collaborative Beamforming (CB) can improve energy efficiency and its transmission range in Wireless Sensor Networks (WSNs). Traditional optimizttion methods have high computational complexity and implementation overhead, which challenge the practical applications of WSNs. In this paper, we first present a beampatten optimizttion problem of CB communication for WSNs. We then treat the beampattern optimizttion of CB as a dynamic potential game problem and propose a low-complexity distributed learning (DL) beampattern optimization algorithm based on joint strategy fictitious play. Results of extensive simulation analysis show that the proposed DL algorithm can achieve good beampattern performance and low average interference-noise-ratio (INR) in the directions of unintended base stations. Moreover, this algorithm has low complexity on each collaborative node for WSNs.