基于HMM的信源—信道迭代联合译码

提出一种在接收端利用Turbo译码软输出,结合HMM（隐马尔可夫模型）中的Baum-Welch重估算法获取信源模型参数并进行信源-信道迭代联合译码的算法.通过含噪接收序列信道译码后的软输出对信源模型参数进行估计,并将迭代估计获得的信源精确概率结构和信道译码结合进行信源-信道联合迭代译码.同时从信息论角度提出用鉴别信息来度量估计获得的信源模型参数的精度,以及确定迭代估计终止的条件.

Joint source-channel iterative decoding based on hidden markov model

A joint source-channel decoding algorithm using source parameters which were estimated by the soft output of Turbo code with Baum-Welch reestimated algorithm was proposed. The source parameters were obtained by the soft output of decoding the received noisy information sequence. The joint source-channel iterative decoding was implemented by combining the channel decoding and the source decoding with accurate probability structure of source model estimated by iteration. Discrimination information was suggested to measure the precision of the estimated source parameters and was used to determine the stop of the estimation iteration.