大约束度卷积码快速译码方法的研究  

Research of fast decoding for longer constraint length convolutional codes

作　　者：黄肖玲[1] 杨华龙[1] 

机构地区：[1]大连海事大学交通运输管理学院,辽宁大连116026

出　　处：《通信学报》2010年第3期57-64,共8页Journal on Communications

基　　金：辽宁省教育厅高等学校科研基金资助项目(2009A312);国家自然科学基金资助项目(50875042)~~

摘　　要：针对Viterbi译码算法的计算复杂度随着卷积码约束长度的增加呈指数增加,译码延迟过大,只适用于约束长度较小的卷积码译码的缺陷,提出了适用于大约束度的卷积码译码方法。采用了改进粒子群优化算法,弥补传统粒子群优化算法在解决离散问题方面的缺陷——对卷积码快速译码。该方法通过设定种群规模M来确定译码路径数,极大地缩小了译码网格中的路径搜索范围,使译码延迟减小,更适用于约束长度较大的卷积码。还提出了译码宽度自适应的卷积码译码方法,对Viterbi译码算法进行了改进,把固定的译码路径宽度改进为随信道噪声的变化而变化,大大降低译码计算复杂度。仿真实验表明提出的2种译码方法的有效性。To overcome the disadvantage of Viterbi decoding algorithm, in which its complexity exponentially increases with the increasing constraint length of convolutional codes, and the decoding delay was too large to fit the decoding of longer constraint length convolutional codes, a fast decoding of convolutional codes for longer constraint length, based on improved particle swarm optimization algorithm, was proposed. The proposed method reduces the searching area in the grid of decoding and shortens the decoding delay by setting the population size M to determine the number of decoding path, therefore was more suitable for longer constraint length convolutional codes. Another method of decoding convolu- tional codes based on self-adapting of decoding width was also proposed. Simulation results show that the proposed both methods have advantages in reducing the computational complexity and the decoding time.

关 键 词：卷积码 译码算法 粒子群算法 译码性能 

分 类 号：TN911.22[电子电信—通信与信息系统]