5G beamforming weight optimization method based on particle swarm optimization algorithm - Jianbin WANG; Hengjun WANG; Song WU; Zhenkai WANG (Dianxin kexue)
In order to solve the problems of insufficient indoor 5G signal coverage and difficulty in optimization of high-rise buildings, the 5G beamforming weight optimization method based on particle swarm optimization (PSO) algorithm was proposed.Decoupling and reducing the network dimension into multiple subnet slices by collecting the data reported by the terminal, and the single cell weight database was planned and simulated to create the multi-cells weights group and fitness function.Finally, the PSO algorithm was adopted to obtain the local optimal weight group of the multi-cells.The test results show that the reference signal receiving power (RSRP) is improved by 8.7%, the signal to interference plus noise ratio (SINR) is improved by 17.5%, the downlink throughput is promoted by 27.3% together.The proposed method has the advantages of low cost, high efficiency and intelligence, and can significantly improve the user perception in high-rise buildings.