SIMO信道组合优化递推序列检测算法

A Recursive Approach of Combined Optimization to Sequence Detection of SIMO Channels

传统的盲均衡算法主要基于高阶统计量(HOS)法或信道输出过采样的二阶统计量 (SOS)算法,而这些算法不能实际应用于时变环境。与现有的自适应均衡LMS算法、RLS算法不同,提出了一种基于有限字符集信息的组合递推算法,实现单输入多输出 (SIMO)信道盲序列检测。仿真表明:该算法具有较快的收敛速度和较低的稳态误码。

Conventional blind equalization algorithms are based on high-order statistics or on the over-sampled channel output, but these algorithms couldn't be practically applied in time-varying environment. Different from present adaptive equalization algorithms based on LMS and RLS, this paper proposes a new recursive algorithm of combined optimization to blindly detect the sequence of single-input multiple-output (SIMO) channels. This algorithm is based on the information of finite alphabet. Simulation results show that this approach delivers rapid convergence and low steady-state error.