A FAM-2D RLS based smart Massive MIMO system

Arun Joy, Athira jess, Irin Sajan, Priscilla Grace
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Abstract

In this paper we implement a Fast Array Multichannel 2D Recursive Least Square (FAM 2D-RLS) based smart antenna system for massive MIMO. A rectangular antenna array in the X-Y plane is considered. The direction of arrival (DOA) is estimated using MUSIC algorithm. The estimated DOA is used by the adaptive beamformer to generate beams that have maximum gain in the direction of receiver and nulls in the direction of interferes. The computational complexity is calculated and convergence performance is simulated and compared with standard adaptive algorithms. It is seen that convergence performance of FAM 2D-RLS is similar to that of a standard RLS algorithm while the computational complexity is comparable to that of standard Least Mean Square algorithm (LMS). It is also observed that the computational cost of the adaptive filter is directly proportional to the total number of antennas in the antenna array. Hence the contributions in this paper is highly relevant in the case of massive MIMO systems. The simulations are performed in MATLAU & SystemVue.
基于FAM-2D RLS的智能大规模MIMO系统
本文实现了一种基于快速阵列多通道二维递归最小二乘(FAM 2D- rls)的大规模MIMO智能天线系统。考虑了X-Y平面上的矩形天线阵。使用MUSIC算法估计到达方向(DOA)。自适应波束形成器利用估计的DOA产生在接收方向增益最大、在干扰方向增益为零的波束。计算了该算法的计算复杂度,并与标准自适应算法进行了收敛性能的仿真比较。可以看出,FAM 2D-RLS的收敛性能与标准RLS算法相似,而计算复杂度与标准最小均方算法(LMS)相当。我们还观察到,自适应滤波器的计算成本与天线阵列中的天线总数成正比。因此,本文的贡献与大规模MIMO系统的情况高度相关。仿真在MATLAU和SystemVue中进行。
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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