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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。
In order to solve the problem that the traditional linear block code recognition method is not suitable for the low density parity check (LDPC) code with longer code length, the ant colony algorithm is used to optimize the dual space search, and the recognition of LDPC codes is completed. The recognition model of atmospheric laser communication channel model and LDPC code is established, and the expression of log-likelihood ratio function of calibration relationship under atmospheric laser communication turbulence channel is given. Combining the basic ant colony algorithm and LDPC code recognition problem, The Likelihood Ratio function is processed as an objective function to identify the LDPC code by iteratively iterating the optimal objective function value and the best search path in each search process. Simulation results show that when the code length is 256, under the condition of weak turbulence, the recognition rate can reach 78% when the SNR is not less than 8dB. Under the condition of strong turbulence, when the SNR is no less than 10dB, Recognition rate up to 77%. In addition, the parameter setting in the ant colony algorithm has a greater impact on the performance of the algorithm, and should be selected according to the actual situation.