一种基于Gauss-Seidel迭代的高效大规模MIMO检测算法
首发时间:2020-02-19
摘要:目前大规模多输入多输出(MIMO)系统是5G及未来无线通信中最有前途的技术之一。在大规模MIMO信号检测中需要实现大量的矩阵计算,特别是矩阵求逆计算。本文在基于迭代算法求解线性方程以化简MMSE矩阵求逆的基础上,提出优化初始解应用于迭代算法以达到提升检测性能的目的。仿真结果表明,迭代算法在采用本文所提出的优化初始解后可迭代更少次数达到传统迭代算法的检测性能,通过几次迭代后优化算法能够快速收敛并达到接近MMSE的检测性能,并将算法的计算复杂度保持在 ,与MMSE相比将计算复杂度降低一个量级。
关键词: 大规模MIMO Gauss-Seidel迭代 Jacobi迭代 优化初始解 低复杂度
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A novel efficient detection algorithm based on Gauss-Seidel method for massive MIMO system
Abstract:Currently, the massive multiple-input multiple-output (MIMO) system is one of the most promising wireless transmission technologies for 5G and beyond. Massive MIMO requires implementing large-scale matrix computations, especially for matrix inversion. In this paper, a novel detection algorithm is proposed based on iterative algorithmsolving linear equation to simplify the inverse of MMSE matrix.The optimal initial solution is applied to iterative algorithms to improve the detection performance. The simulation results show that the optimized iterative algorithms can achieve the detection performance of the traditional iterative algorithm with fewer iterations. After several iterations, the optimized algorithm can quickly converge and achieve the detection performance close to MMSE. Meanwhile, the computational complexity of the optimized algorithm keep consistently of , which reduced by an order of magnitude compared with MMSE.
Keywords: massive MIMO Gauss-Seidel iterative Jacobi iterative optimized initial solution low-complexity
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