大规模MIMO系统中全局LAS检测算法  

Global optimal LAS detection algorithm in massive MIMO systems

作　　者：张维 周围[1,2] ZHANG Wei;ZHOU Wei(College of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;Chongqing Key Laboratory of Mobile Communications Technology,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065 [2]重庆邮电大学移动通信技术重庆市重点实验室,重庆400065

出　　处：《南京邮电大学学报（自然科学版）》2020年第4期37-43,共7页Journal of Nanjing University of Posts and Telecommunications：Natural Science Edition

基　　金：国家自然科学基金(61771085);重庆市基础与前沿研究计划(CSTC2015icyjA40040)资助项目。

摘　　要：在大规模多输入多输出(Multiple Input Multiple Output,MIMO)系统中,现有的非线性检测算法中似然上升搜索(Likelihood Ascend Search,LAS)算法的复杂度较低,但是算法容易陷入局部极值,导致算法性能较差。文中提出一种全局最优的模拟退火-似然上升搜索(Simulated Annealing-Likelihood Ascend Search,SA-LAS)算法,该算法引入模拟退火算法中的概率因素,以一定概率接收相对更差的解,从而改进算法的局限性。同时还利用加权-对称连续超松弛(Weighted Symmetric Successive Over Relaxation,WSSOR)迭代处理复杂的矩阵求逆运算,降低初始解的求解复杂度;另外,设置多个邻域候选集并行搜索加快搜索的速度;最后设置双阈值控制迭代终止时间,以此降低算法复杂度。理论分析了该算法的复杂度,并通过仿真对不同检测算法的误码率性能和收敛速度进行了研究,结果表明:在复杂度阶数不增加的情况下,文中提出的SA-LAS检测算法的误码率性能明显优于现有的LAS检测算法。In the massive multiple input multiple output(MIMO)system,the likelihood ascend search(LAS)algorithm in the existing nonlinear detection algorithms has lower complexity,but it is easy to fall into local optimum,resulting in poor performance of the algorithm.This paper proposes a globally optimized simulated annealing-likelihood ascend search(SA-LAS)algorithm.The algorithm introduces the probability factor in the simulated annealing algorithm,which can receive a relatively worse solution with a certain probability,thus improving the limitations of the algorithm.Meanwhile,the weighted symmetric successive over relaxation(WSSOR)iteration is used to deal with complex matrix inversion operations,thus reducing the complexity of solving the initial solution.In addition,multi-neighbor search candidate sets are set to parallel search to speed up the search speed;Finally,a double threshold is set to control the iteration termination time,reducing the complexity of the algorithm.The complexity of the algorithm is theoretically analyzed,and the bit error rate performances and the convergence speeds of different detection algorithms are studied by a simulation.The results show that the performance of the global optimal detection algorithm is significantly better than that of the existing nonlinear detection algorithm when the complexity order is not increased.

关 键 词：大规模多输入多输出 似然上升搜索 模拟退火 全局最优 WSSOR 多邻域候选集 双阈值 

分 类 号：TN929.5[电子电信—通信与信息系统]