IRS辅助大规模MIMO系统中抑制残余硬件损伤的AQBFO无源波束赋形方案

AQBFO-Based Passive Beamforming Scheme for Intelligent Reflecting Surface-Aided Massive MIMO Systems with Residual Hardware Impairments

由通信收发机硬件非理想特性导致的残余硬件损伤在智能反射面(Intelligent reflecting surface,IRS)辅助的大规模多输入多输出(Multiple-input multiple-output,MIMO)系统中难以避免,并且会严重降低上行用户的可达和速率。针对这一问题,本文提出了一种基于自适应量子菌群觅食优化(Adaptive quantum bacterial foraging optimization,AQBFO)算法的无源波束赋形方案,用于抑制残余硬件损伤对系统性能的影响。首先,基于统计信道状态信息(Channel state information,CSI)推导出系统上行可达和速率的近似解析表达式。然后,以最大化和速率为目标,基于AQBFO算法对无源波束赋形进行优化。仿真结果验证了在IRS辅助大规模MIMO系统中,基于AQBFO算法的无源波束赋形方案能够有效抑制残余硬件损伤的影响,并显著提升系统的上行遍历和速率。

The residual hardware impairments(HWIs)caused by the non-ideal characteristics of the transceiver hardware is unavoidable in the intelligent reflecting surface(IRS)assisted massive multipleinput multiple-output(MIMO)system,which seriously affects the uplink achievable rate.To solve this problem,a passive beamforming scheme based on the adaptive quantum bacterial foraging optimization(AQBFO)algorithm is proposed to suppress the negative impact of HWIs on the system performance.Firstly,an approximate analytical expression of the uplink achievable rate is derived based on statistical channel state information(CSI).Then,the passive beamforming optimization scheme based on AQBFO algorithm is carried out to maximize the sum rate.Simulation results show that in IRS-assisted massive MIMO system,the passive beamforming scheme based on AQBFO algorithm can effectively suppress the influence of residual HWIS and significantly improve the uplink ergodic sum rate.