Sidelobe reduction and capacity improvement of open-loop collaborative beamforming in wireless sensor networks

Abstract

Collaborative beamforming (CBF) with a finite number of collaborating nodes (CNs) produces sidelobes that are highly dependent on the collaborating nodes' locations. The sidelobes cause interference and affect the communication rate of unintended receivers located within the transmission range. Nulling is not possible in an open-loop CBF since the collaborating nodes are unable to receive feedback from the receivers. Hence, the overall sidelobe reduction is required to avoid interference in the directions of the unintended receivers. However, the impact of sidelobe reduction on the capacity improvement at the unintended receiver has never been reported in previous works. In this paper, the effect of peak sidelobe (PSL) reduction in CBF on the capacity of an unintended receiver is analyzed. Three meta-heuristic optimization methods are applied to perform PSL minimization, namely genetic algorithm (GA), particle swarm algorithm (PSO) and a simplified version of the PSO called the weightless swarm algorithm (WSA). An average reduction of 20 dB in PSL alongside 162% capacity improvement is achieved in the worst case scenario with the WSA optimization. It is discovered that the PSL minimization in the CBF provides capacity improvement at an unintended receiver only if the CBF cluster is small and dense.