为了减少MAP算法的复杂度 ,可以采用减状态或减搜索技术 .本文提出了一种完全基于M算法原理、应用于Turbo均衡的减少搜索的软输出检测算法 ,它是一种次最佳的Lee算法 .该算法称为软输出M算法 (SO M 算法 ) ,它同时在Lee算法的前向迭代及扩展前向迭代中采用了M策略 .计算机仿真结果表明 ,通过适当选择和调整Turbo均衡迭代过程中算法的广度参数和深度参数 ,该算法可获得较好的性能与复杂度的折衷 . In order to reduce the complexity of the MAP algorithm, the state reduction or the search reduction technique can be used.In this paper, a reduction search-based soft output detection algorithm based on the principle of M algorithm and applied to Turbo equalization is proposed, which is a sub-optimal Lee This algorithm is called soft output M algorithm (SO M algorithm), and it uses M strategy in forward iteration and extended forward iteration of Lee algorithm at the same time.Computer simulation results show that by choosing and adjusting Turbo equalization iterative process The algorithm’s breadth and depth parameters, the algorithm can get better performance and complexity of the compromise.