带判决反馈的盲最大似然序列估计

本文提出了一种新型的带有判决反馈的减小状态最大似然序列估计ＲＳＳＤＦＰＳＰ,新算法带有两个信道估值器并且可以工作在盲环境下．使用最大似然序列估计（ＭＬＳＥ）来处理信道冲激响应的前导干扰及主径,反馈滤波器处理后尾干扰,并且用ＰｅｒＳｕｒｖｉｖｉｎｇＰｒｏｃｅｓｉｎｇ（ＰＳＰ）算法来得到ＭＬＳＥ部分的信道冲激响应,信道估值器２得到后尾干扰．计算机模拟表明,这种ＲＳＳＤＦＰＳＰ方案在减小ＭＬＳＥ的计算复杂度的同时能最大限度地得到ＭＬＳＥ的性能,是ＭＬＳＥ在计算复杂度与性能之间的较好折中．

Blind Maximum-Likelihood Sequence Estimation with Decision Feedback

This paper presents a new reduced state,decision feedback Viterbi equalizer (RSSDF PSP) with two channel estimators and it works in blind.RSSDF PSP uses maximum likelihood sequence estimation (MLSE) to handle the precursors and the main cursor and the decision feedback filter to handle the post cursors.The channel estimator 1 obtains the precursors and the main cursor by the Per Surviving Processing techniques;the channel estimator 2 obtains the post cursors.Simulation results show that the RSSDF PSP has nearly the same performance as the MLSE.It provides the best tradeoff between complexity and performance of MLSE.