两轮咬尾网格上近似线性时间ML译码
Approximate Linear Time ML Decoding on Tail-Biting Trellises in Two Rounds
摘要：
本文提出了一种在咬尾网格上的线性时间近似最大似然译码算法，它只需要在网格上进行两轮译码。这是一个适应的算法提出了较早的优势，它减少了时间复杂度从O（mlogm）到O（m），其中m是在咬尾网格节点的数量。文中给出了该算法输出不同于理想ML译码器输出的必要条件，并给出了在AWGN信道上对两种存储量分别为4和6的码率1/2卷积码采用截尾算法的仿真结果
英文摘要：
A linear time approximate maximum likelihood decoding algorithm on tail-biting trellises is prsented, that requires exactly two rounds on the trellis. This is an adaptation of an algorithm proposed earlier with the advantage that it reduces the time complexity from O(mlogm) to O(m) where m is the number of nodes in the tail-biting trellis. A necessary condition for the output of the algorithm to differ from the output of the ideal ML decoder is reduced and simulation results on an AWGN channel using tail-biting rrellises for two rate 1/2 convoluational codes with memory 4 and 6 respectively are reported
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
