基于IBED和仿生算法的LT码度分布设计

度分布是影响Luby变换（Luby transform，LT）码性能优劣的关键因素，为了得到更优的度分布，提出一种基于改进的二进制指数分布（improved binary exponential distribution，IBED）和仿生算法的LT码度分布设计方案.采用IBED度分布进行LT编码，初始译码成功率可高达90%以上，但随着译码开销增大，译码成功率上升速度减缓，而此时鲁棒孤子分布（robust soliton distribution，RSD）的译码性能表现更佳.为了将IBED和RSD的优点有机结合，利用人工鱼群算法（artificial fish swarm algorithm，AFSA）在两种度分布间寻优，基于期望可译集构建该算法的目标函数，通过最大化目标值得到更优的度分布.仿真结果表明，与类似方法及传统的RSD相比，采用新度分布进行LT编码可明显降低译码开销，并节约编译码耗时.

The Design of Degree Distribution for LT Codes Based on IBED and Bionic Algorithm

The degree distribution greatly influences the performance of Luby transform(LT)codes.In order to obtain a better degree distribution,a method is proposed to design the degree distribution for LT codes based on improved binary exponential distribution(IBED)and bionic algorithm.The decoding performance of IBED outperforms robust soliton distribution(RSD)when the overhead is small,and its successful decoding rate reaches more than 90%.The successful decoding rate for IBED rises slowly as the overhead increases,while RSD performs better.In order to combine the advantages of IBED and RSD,we use artificial fish swarm algorithm(AFSA)to search the optimal degree distribution between these two.The expected ripple size is employed to present the objective function for AFSA,and the optimal degree distribution is obtained by maximizing the objective value.Simulation results show that compared to other optimized degree distributions and RSD,the new degree distribution reduces the overhead,and saves the average consuming time per encoding/decoding process.