一种改进SWOMP的大规模MIMO信道估计算法  

Modified SWOMP channel estimation method in massive MIMO system

作　　者：王晓亮 梅进杰[1] 姚禹 孟紫薇 WANG Xiaoliang;MEI Jinjie;YAO Yu;MENG Ziwei(Air Force EarlyWarning Academy,Wuhan 430019,China;No.94326 Unit,the PLA,Jinan 250000,China;No.93277 Unit,the PLA,Shenyang 110141,China)

机构地区：[1]空军预警学院,武汉430019 [2]94326部队,济南250000 [3]93277部队,沈阳110141

出　　处：《空军预警学院学报》2020年第4期279-282,287,共5页Journal of Air Force Early Warning Academy

摘　　要：针对大规模多输入多输出系统(massive MIMO)波束域信道估计中传统算法在低信噪比条件下无法保证较高的估计性能问题,设计了基于改进灰狼优化的分段弱正交匹配追踪(IGWO-SWOMP)压缩感知算法.该算法基于改进的灰狼优化(IGWO)算法自适应获取到大规模多输入多输出系统波束域信道中最小均方误差对应的迭代数与阈值,达到参数自适应设定的目的.仿真结果表明,与传统算法相比,IGWO-SWOMP算法的估计性能明显提高;在波束域角度扩展改变时,IGWO-SWOMP算法实现了自适应信道估计,能够保证较高的估计性能.Aiming at the problem that the traditional algorithm in the estimation of massive MIMO beam domain channel cannot guarantee a relatively higher estimation performance under the condition of low SNR,this paper designs a compressive sensing algorithm based on improved gray wolf optimization stagewise orthogonal matching pursuit(IGWO-SWOMP).This algorithm is based IGWO to adaptively acquires the iteration number and threshold corresponding to the minimum mean square error in the massive MIMO beam domain channel to achieve the purpose of adaptive parameter setting.The simulation results show that the channel estimation performance of IGWO-SWOMP algorithm is improved significantly compared with the traditional algorithm,and that when the angle of the beam domain expands and changes,the IGWO-SWOMP algorithm realizes adaptive channel estimation,which guarantees a relatively higher estimation performance.

关 键 词：压缩感知 大规模多输入多输出技术 改进灰狼优化 分段弱正交匹配追踪算法 

分 类 号：TN929.5[电子电信—通信与信息系统]