基于改进对数正态误差恒模算法的MIMO判决反馈

MIMO Decision Feedback Equalization Based on Improved Log-Normal Error Function CMA Algorithm

对数正态误差恒模算法误差曲线收敛速度快,但均方误差较大。针对这一问题,提出了改进的对数正态误差恒模算法,并将此算法应用于按序串行干扰消除MIMO判决反馈算法中。利用改进的对数正态误差恒模算法来得到前馈数据向量并将其合并到反馈数据向量中,然后按序将已检测并判决出的信号进行消除,避免了已判决出的信号对接收数据向量的干扰。在多散射物的无线通信环境下进行仿真,结果表明与迭代最小二乘按序判决反馈算法相比,所提算法检测性能提高,误码率显著下降。

Log-normal error function CMA algorithm has fast convergence rate, but it incurs large mean square error To solve this problem, an improved log-normal error function CMA algorithm （ILNCMA） was proposed and applied into the ordered successive interference cancellation （ OSIC） MIMO decision feedback equalization （DFE）. The ILNCMA algorithm combined the feedforward data vector with the feedback data vector and cancelled decided symbols from the received symbols successively. The ILNCMA-OSIC-DFE algorithm avoids the interference of the decided symbols and improves the detection performance. In the environment where lots of wireless communications were scattered over, simulation testing and the results show that the detection performance of proposed algorithm is dramatically improved in comparison with the ordered decision feedback equalization based on recursive least square algorithm.