文章基本信息

标题：An Improved Jacobi-Based Detector for Massive MIMO Systems
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作者：Xiaoqing Zhao ; Zhengquan Li ; Song Xing 等
期刊名称：Information
电子版ISSN：2078-2489
出版年度：2019
卷号：10
期号：5
页码：165-178
DOI：10.3390/info10050165
出版社：MDPI Publishing
摘要：Massive multiple-input-multiple-output (MIMO) is one of the key technologies in the fifth generation (5G) cellular communication systems. For uplink massive MIMO systems, the typical linear detection such as minimum mean square error (MMSE) presents a near-optimal performance. Due to the required direct matrix inverse, however, the MMSE detection algorithm becomes computationally very expensive, especially when the number of users is large. For achieving the high detection accuracy as well as reducing the computational complexity in massive MIMO systems, we propose an improved Jacobi iterative algorithm by accelerating the convergence rate in the signal detection process.Specifically, the steepest descent (SD) method is utilized to achieve an efficient searching direction. Then, the whole-correction method is applied to update the iterative process. As the result, the fast convergence and the low computationally complexity of the proposed Jacobi-based algorithm are obtained and proved. Simulation results also demonstrate that the proposed algorithm performs better than the conventional algorithms in terms of the bit error rate (BER) and achieves a near-optimal detection accuracy as the typical MMSE detector, but utilizing a small number of iterations.
关键词：the massive MIMO system; Jacobi algorithm; the steepest descent method; the whole-correction method; signal detection the massive MIMO system ; Jacobi algorithm ; the steepest descent method ; the whole-correction method ; signal detection