Node selection optimization for collaborative beamforming in wireless sensor networks

The communication distance and the energy of the nodes are limited in large-scale wireless sensor networks (WSNs). Collaborative beamforming is an effective way to solve such problem. However, the distribution of node location is not uniform, which leads to poor performance of the mainlobe and causes the high sidelobe level (SLL). This paper presents a novel collaborative communication method based on node selection optimization algorithm (NSOA). The method to calculate the optimal number of array nodes and to select the optimal array nodes for setting up a virtual antenna array are shown in NSOA. NSOA has the ability to select the CB nodes with optimal excitation amplitude and excitation phase by firefly algorithm to obtain the optimal radiation beampattern. In addition, energy consumption and communication delay of the nodes can be reduced. Simulation results show that the maximum SLL of the radiation beampattern obtained by NSOA is lower comparing with those obtained by the CCB and CSNA, meanwhile, the convergence rate of NSOA is faster than that of CCB. Compared with the traditional clustering routing algorithm, NSOA has advantages in terms of communication delay, energy consumption, and prolonging network lifetime. © 2015 Elsevier B.V. All rights reserved.