Performance Analysis of 3D Linear and Circular Array Optimized by Imperialist Competitive Algorithm

Collaborative beamforming (CB) can enhance communication reliability and energy efficiency of Wireless Sensor Networks (WSNs). However, careful node selection is required to reduce the peak sidelobe level (SLL) of CB to reduce interference during transmission. Prior studies have proposed mapping of array onto WSNs environment to select the appropriate nodes to perform CB. Nevertheless, the mapped arrays only perform CB in azimuth direction. The contribution of this paper is the designation of improved fitness function to suppresses peak SLL and control beamwidth size of beampattern in both azimuth and elevation directions. The proposed fitness function is used to evaluate the inter-element spacing of circular and linear arrays optimized by Imperialist Competitive Algorithm (ICA). The performance of arrays is evaluated in terms of beamwidth size, average peak SLL, stability, execution time and convergence behavior. The results show that linear array gives the best average peak SLL suppression of 67.8% compared to circular array. Besides, linear array shows consistency in suppressing peak SLL of beampattern with faster execution time and less iteration than circular array.