基于蚁群算法的大气激光通信中低密度奇偶校验码的盲识别  

Blind Identification of LDPC Codes in Atmosphere Laser Communication Based on Ant Colony Algorithm

作　　者：孙韩[1] 郝士琦[1] 张岱[1] 赵青松[1] 王勇[1] 

机构地区：[1]电子工程学院脉冲功率激光技术国家重点实验室,安徽合肥230037

出　　处：《光学学报》2016年第9期70-75,共6页Acta Optica Sinica

基　　金：国家自然科学基金(61571446);安徽省自然科学基金(1308085MF83;1408085MF120)

摘　　要：针对传统线性分组码识别方法对码长较长的低密度奇偶校验(LDPC)码不适用的情况,利用蚁群算法对对偶空间进行优化搜索,完成了对LDPC码的识别。建立了大气激光通信信道模型和LDPC码的识别模型,给出了大气激光通信湍流信道下校验关系对数似然比函数表达式;将基本蚁群算法与LDPC码的识别问题结合,将对数似然比函数经过处理作为目标函数,通过不断迭代每次搜索过程中目标函数最优值和最佳搜索路径,实现对LDPC码的识别。仿真结果表明:当码长为256时,在弱湍流条件下,当信噪比不低于8dB时,识别率可达78%;在强湍流条件下,当信噪比不低于10dB时,识别率可达77%。此外,蚁群算法中的参数设置对算法性能有较大影响,应根据实际情况加以选择。Given the fact that traditional linear block code identification methods cannot be applied to low density parity check （LDPC） codes, an ant colony algorithm is adopted to optimize the dual space search, so as to realize the LDPC code identification. The atmospheric laser communication channel model and the LDPC codes identification model are established, and the logarithmic likelihood ratio function of calibration relationship under the turbulent atmosphere channel is given. Then the basic ant colony algorithm is combined with LDPC code identification, the logarithmic likelihood ratio function is transformed into the objective function, and the recognition of LDPC codes is realized through continuous iteration for optimal value and optimal search path in the process of ants searching. The simulation results show that under the condition of 256 code length and weak turbulence, when the signal-to-noise ratio （SNR） is not less than 8 dB, the recognition rate can reach 78% ; under strong turbulence, when the SNR is not less than 10 dB, the recognition rate can reach 77%. In addition, the parameter settings in the ant colony algorithm have a great influence on the algorithm performance and should be chosen according to actual situations.

关 键 词：光通信 低密度奇偶校验码识别 蚁群算法 优化搜索 

分 类 号：TN919[电子电信—通信与信息系统]