An Improved Cuckoo search Algorithm for Optimizing the Beam Patterns of the Random Antenna Arrays

摘要

Collaborative beamforming (CB) techniques have been introduced in wireless sensor networks to improve the transmission distance of a single sensor node. The biggest challenge for using CB is how to suppress the high sidelobe level (SLL). In this paper, an improved cuckoo search algorithm (IPCS) is proposed. In the case of optimizing the position coordinates of the array nodes, the dynamic adjustment of the discovery probability and an improved adaptive strategy of step size parameter are designed, to improve the convergence rate and the local searching ability of conventional CS algorithm, thereby making it suitable for optimizing the beam patterns of the distributed random antenna array (RAA). The performance of this novel method is compared with other intelligent optimization algorithms. Simulation results show that the proposed algorithm achieve better performance in terms of SLL suppression.