An adaptive filter based channel estimation framework for large MIMO systems

A.Ramya Sree, H. Varghese, Arun Joy
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Abstract

In this paper an adaptive filter based channel estimation framework is introduced for large MIMO systems. The adaptive algorithms used are Least Mean Square (LMS) and Recursive Least Square (RLS). The system model considered is Centralised Antenna System (CAS). The convergence performance of both LMS and RLS based channel estimation is simulated and the computational complexity of each algorithm is computed. The convergence performance of LMS adaptive channel estimation w.r.t varying step size is studied and similarly the convergence performance of RLS adaptive channel estimation w.r.t varying forgetting factor and regularisation factor is studied.
基于自适应滤波器的大型MIMO系统信道估计框架
针对大型MIMO系统,提出了一种基于自适应滤波器的信道估计框架。采用的自适应算法有最小均方(LMS)和递归最小二乘法(RLS)。所考虑的系统模型是集中式天线系统(CAS)。仿真了基于LMS和基于RLS的信道估计的收敛性能,并计算了每种算法的计算复杂度。研究了随步长变化的LMS自适应信道估计的收敛性能,同样研究了随遗忘因子和正则化因子变化的RLS自适应信道估计的收敛性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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