基于IPSO-LMMSE算法的信道估计仿真与实现  

Simulation and implementation of channel estimation based on IPSO⁃LMMSE algorithm

作　　者：蔡云浩 刘祖深 许虎 CAI Yunhao;LIU Zushen;XU Hu(North University of China,Taiyuan 030051,China;CETC Ceyear Technologies(Anhui)Co.,Ltd.,Bengbu 233010,China;Bengbu Technology Innovation Center on Electronic Measurement Instrumentation Technology,Bengbu 233010,China)

机构地区：[1]中北大学,山西太原030051 [2]中电科思仪科技(安徽)有限公司,安徽蚌埠233010 [3]电子测量仪器技术蚌埠市技术创新中心,安徽蚌埠233010

出　　处：《现代电子技术》2023年第23期23-27,共5页Modern Electronics Technique

摘　　要：WiFi7作为一种新型的高速无线局域网技术,被广泛应用于各种移动设备中。在WiFi系统中,信道会受到各种影响,例如时变和多路径传播频率选择性衰落、信号衰减、反射和强噪声干扰效应,这些影响会显著降低系统性能。因此,信道估计成为重要环节,其结果直接影响到系统的性能和可靠性。文中提出改进的粒子群优化(IPSO)算法,通过改变传统PSO算法惯性权重的计算方式,与线性最小均方误差算法(LMMSE)结合使用。实验结果表明,在信噪比相同的条件下,改进后算法的MSE、BER、EVM等指标相较于传统LMMSE算法有显著提升,并且该方法应用于国产矢量信号分析软件VSA中,具有较好的实用性和应用前景。WiFi7,as a new high⁃speed WLAN technology,is widely used in various mobile devices.In WiFi systems,the channel is subjected to various influences,such as time⁃varying and multipath propagation frequency⁃selective fading,signal attenuation,reflection,and strong noise interference effects,which degrade system performance seriously.Therefore,channel estimation plays a crucial role,as its results impact the performance and reliability of the system directly.In this paper,an improved particle swarm optimization(IPSO)algorithm is proposed,which combines the traditional PSO algorithm with the linear minimum mean square error(LMMSE)algorithm by modifying the calculation method of the inertia weight.Experimental results demonstrate that under the same signal⁃to⁃noise ratio(SNR),the improved algorithm achieves significant improvements in metrics such as mean square error(MSE),bit error rate(BER)and error vector magnitude(EVM)in comparison with the traditional LMMSE algorithm.Moreover,this method is applied in domestic vector signal analysis(VSA)software,showing promising practicality and application prospects.

关 键 词：WiFi7 信道估计 粒子群优化 IPSO LMMSE 信号分析 

分 类 号：TN921-34[电子电信—通信与信息系统]