该文通过分析安全编码的原理推导了安全间隙约束条件下高斯窃听信道保密速率的计算方法，并根据置信传播(Belief Propagation, BP)译码算法及其改进算法，针对基于中短码长LDPC码所设计的安全编码提出一种2维信息修正的分类归一化最小和译码算法。该算法先将输入校验节点信息绝对值分成最小值和次小值两类，然后在译码初始化时利用概率统计理论分别推导出相应的最佳归一化因子对分类后的信息进行修正。仿真结果表明，该算法在高信噪比区域的译码性能高于BP算法和归一化最小和算法，低信噪比区域误比特率迅速逼近0.5，且能减小不同安全编码速率LDPC码的安全间隙，提高了保密信息安全传输的性能。%This paper analyzes the mechanism of physical layer secrecy coding and calculates the secrecy rate for the Gaussian wiretap channel under the security gap constraint. Furthermore, a classified normalized decoding algorithm with two-dimensional information correction based on Belief Propagation (BP) algorithm and its improvements for the short and medium block length Low Density Parity Check (LDPC) based secrecy codes is presented. The algorithm first utilizes classification according to the absolute values of incoming messages in check nodes. Then it uses 2-dimensional normalization to correct the minimum and sub-minimum values. The 2-dimensional normalized factors can be calculated respectively by using probability and statistic theory in the initialization step. Simulation results show that the proposed algorithm achieves better performance than BP algorithm and normalized BP-based algorithm at the high SNR, but the bit error radio gets close to 0.5 rapidly at the low SNR. It can reduce security gap of LDPC-based secrecy codes with different secrecy rates efficiently.
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