中文摘要：

本文提出了一种缩放软信息的Max-Log-MAP迭代均衡算法（Scaled Max—Log-MAP，SMLM）的性能，并分析了它对SNR估计误差的敏感性问题，结果表明在低损失信道上，SMLM算法能有效改善Max-Log—MAP（ULM）迭代均衡算法的性能，并不受SNR估计误差的影响．考虑到在初始迭代，MLM硬判决结果可能有错误，本文还提出了一种改进的由MLM切换到LM的均衡算法，大大改善了未进行SNR校正时的误码性能．最后，本文还建议了一种由SMLM切换至LM的迭代均衡算法，它进一步改善了高损失信道上迭代均衡系统的性能，尽管本文建议的两种切换均衡算法均不需要任何导引开销。

英文摘要：

In this paper,a Scaled Max-Log-MAP （SMLM） iterative equalization algorithm is proposed,and its sensitivity to SNR mismatch is also studied. The results show that SMLM algorithm performs much better than MINI, in addition to insensitivity to SNR errors,especially over low-loss channels. Then taking account of the possible hard-decision errors after first a few iterations using MINI algorithm,an improved switching turbo equalization algorithm between MINI and LM is presented,by which the performance is improved dramatically compared to that without SNR correction. Finally, based on the fact of insensitivity of SMLM algorithm to SNR mismatch, a new switching equalization algorithm between SMLM and LM is also given. The simulation results show that this new algorithm can further not only improve the system performance,but reduce the complexity of systems,although it does not need any pilot symbols as well.