用遗传算法优化Turbo码交织器

具有短帧的Turbo码的性能取决于交织器的设计．设计的主要目标是距离谱的优化。本文提出在S随机交织器的基础上，用遗传算法(GA)优化交织器．提高Turbo码的自由距离并减少具有自由距离码字的出现频率。它利用了遗传算法的群体多样性，具有全局优化能力的特点，优化了Turbo码的距离谱，提高了系统性能。仿真结果表明，遗传交织器的性能优于块交织器、螺旋交织器等传统交织器。

Interleaver of Turbo Code Optimization Using Genetic Algorithms

The performance of Turbo codes with short block length depends on the interleaver design. A major criteria in the design of an interleaver is the distance spectrum of the code. This paper describes a new interleaver design for Turbo codes based on the criteria using genetic algorithms (GAs). The new interleaver is called genetic interleaver. To speed up the convergence, S-random interleavers are used as an initial population. With the good diversity, wide search region and global optimal ability of GA, the free distance of Turbo code is maximized and a multiplicity of code words with free distance is decreased. Simulation results show that the performance of genetic interleaver outperforms that of the traditional interleavers, such as the block interleaver and the heliblock interleaver.