误码条件下的IRA码盲识别算法

doi:10.3969/j.issn.1001-2400.2017.06.002

摘要/Abstract

摘要：

针对误码条件下非规则重复累积码校验矩阵难以逆向重建以及大规模复杂交织难以恢复的问题，提出了一种基于对偶空间的校验矩阵与交织映射关系识别算法．通过秩准则法识别码长和同步起始点，利用矩阵变换的方法来获取对偶向量，由设定的决策门限从对偶向量中筛选出有效校验向量，并根据非规则重复累积码校验矩阵的稀疏特性，由有效校验向量稀疏化重建出校验矩阵．最后根据非规则重复累积码的编码结构特点识别出交织映射关系．仿真结果表明，该识别算法具有较低的计算复杂度，能够在误码条件下盲估计出编码参数，实现非协作场合的非规则重复累积码盲识别．

关键词: 盲识别, 对偶向量, 信道编码, 非规则重复累积码

Abstract:

For noisy environment, the parity-check matrix of Irregular Repeat-Accumulate(IRA) codes is hard to reconstruct, moreover, the relationships of the large-scale complex interleaver are hard to recover. To solve the problems, a novel blind recognition algorithm is proposed. First, the code's length and synchronization are identified by applying rank criteria. Second, by implementing matrix transformation, the dual vectors of codewords are found. Then, by setting a threshold, the effective parity-check vectors of dual space are selected. According to the sparse characteristics of the IRA codes' parity-check matrix, the parity matrix can be reconstructed with effective parity-check vectors Finally, relationships of the interleaver can be recovered according to the characteristics of IRA codes. Simulation results show that the proposal can be used to estimate IRA codes encoding parameters and complete the blind recognition in the non-cooperative context with noise.

Key words: blind recognition, dual vectors, channal coding, irregular repeat-accumulate codes

陈健;郭永斌;王艳涛;阔永红. 误码条件下的IRA码盲识别算法[J]. 西安电子科技大学学报, 2017, 44(6): 8-13.

CHEN Jian;GUO Yongbin;WANG Yantao;KUO Yonghong. Blind recognition algorithm for IRA codes in noisy environment[J]. Journal of Xidian University, 2017, 44(6): 8-13.

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