A Preconditioned Symmetric Successive Over Relaxation Method for Massive MIMO Signal Detection

Xin-yi Wang, Zhongtao Zhu, Xiaozhang Zhu
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Abstract

For a given massive multiple-input multiple-output (MIMO) systems, how to achieve near-optimal performance with low system complexity is crucial for practical usage. To solve this problem, a new preconditioned symmetric successive over relaxation (SSOR) for minimum mean square error (MMSE) method is introduced in this paper, and the simulation results are compared with other common approaches. The preconditioned process is based on NS method which is found to be able to produce accurate enough initial guess that can be used to improve the convergence rate in the subsequent SSOR processing. The simulation results show that the combined system is improved in convergence rate with limited affect in complexity and bit error rate (BER).
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海量MIMO信号检测的预条件对称逐次过松弛方法
对于给定的大规模多输入多输出(MIMO)系统,如何在较低的系统复杂度下实现近乎最优的性能是实际应用的关键。为了解决这一问题,本文提出了一种新的预处理对称连续过松弛(SSOR)最小均方误差(MMSE)方法,并将仿真结果与其他常用方法进行了比较。基于NS方法的预处理过程能够产生足够精确的初始猜测,可以用于提高后续SSOR处理的收敛速度。仿真结果表明,在对系统复杂度和误码率影响有限的情况下,提高了系统的收敛速度。
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