【摘要】 针对采用计算机穷举法进行删余卷积码好码搜索无法满足更高码率和更大约束长度的问题,提出一种基于量子遗传算法快速搜索删余卷积码好码的方法.通过量子比特编码和量子旋转门更新等方式实现适应度函数的优化求解,得到删余卷积码好码的生成多项式和删余矩阵.搜索结果表明,与计算机穷举法相比,该方法不仅收敛速度快,且灵活性较好.更多还原

【Abstract】 Currently,the search of good punctured convolutional code( PCC) is mainly based on exhaustive search. Nevertheless,the computational complexity of exhaustive search increases exponentially as the number of encoder’s input or the constraint length increases. Therefore,the use of exhaustive search codes is limited in cases of with high bit rates and great constraint lengths. To solve the problem,a new method based on quantum genetic algorithm is proposed for searching good PCCs. The new method optimizes the fitness function through quantum bits encoding and quantum revolving door updating. The experimental results show that the proposed method not only converges quickly but also has good flexibility when compared to exhaustive search.更多还原