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针对K-best检测算法易将最优路径舍去的特点和K-best检测算法搜索星座图中所有点的特点,提出一种性能改进型K-best检测算法和几种降低复杂度K-best检测算法.性能改进型K-best检测算法在进行QR分解之前对信道矩阵进行最小均方误差(MMSE)滤波,能有效减小最优路径被舍弃的概率,提高算法性能;降低复杂度K-best检测算法采用类似球形译码检测的方法减少搜索星座图中点的个数.仿真结果显示,性能改进型K-best检测算法比基于排序QR分解(SQRD)的K-best检测算法有1dB的性能增益.降低复杂度K-best检测算法在K=4时有性能损失;当K=8时,降低复杂度K-best检测算法和原K-best检测算法有同样的性能,同时前者比后者需要更少的计算量.
In view of the characteristic that K-best detection algorithm tends to round off the optimal path and the K-best detection algorithm to search for all the points in the constellation, a performance improvement K-best detection algorithm and several K-best reduction algorithms are proposed. Detection algorithm.The improved K-best detection algorithm performs minimum mean square error (MMSE) filtering on the channel matrix before performing QR decomposition, which can effectively reduce the probability of the optimal path being discarded and improve the performance of the algorithm; reduce the complexity of the K- best detection algorithm uses a similar method of spherical decoding detection to reduce the number of points in the search constellation. Simulation results show that the performance-improved K-best detection algorithm is 1dB better than the K-best detection algorithm based on rank QR decomposition (SQRD) Performance Gain. Reduced Complexity K-best detection algorithm has performance loss when K = 4; reduces complexity when K = 8 K-best detection algorithm has the same performance as the original K-best detection algorithm, Need less computation.