Collaborative Beamforming of UAV Based on Genetic Algorithm

Abstract

Aiming at the problems of short standby time and limited beam coverage in collaborative communication of UAVs, a collaborative beamforming method of UAV based on genetic algorithm is proposed. Based on the random antenna array theory, this method establishes the UAV collaborative beamforming system model, takes the minimum sidelobe level as the optimization goal, and obtains the optimal beam pattern by using genetic algorithm (GA) combined with the selection of optimal node position and optimal beamforming coefficient respectively. The performance comparison of beam pattern with phase error among nodes is analyzed. The simulation results show that the proposed method can effectively improve the beam gain in the target direction, can reduce the peak sidelobe level of the beam pattern, and improve the communication capacity. Among them, the genetic algorithm based on coefficient optimization can reduce the transmission power of each UAV node, save the energy consumption of UAV, and greatly increase the working time of UAV.

Keywords

• |uavs|collaborative beamforming|genetic algorithm|node selection|coefficient optimization