关键词: 信道编码, LDPC码, 盲识别, 校验向量, 稀疏化, 开集识别, 误比特率

Abstract:

A strong fault tolerance algorithm was proposed for LDPC (Low-Density Parity-Check) code reconstruction without a candidate set in a non-cooperative context. The algorithm uses Gauss Jordan elimination to find related columns with low Hamming weight and obtains the parity-check vector of LDPC codes according to the constraint relationship contained in the related column. Then the error code corresponding to the "1" position in the related column is removed. If the iteration according to Gauss Jordan elimination and the removing of error code can not get more parity-check vectors, then it makes these resulting parity-check vectors to be sparse and uses the sparse vectors to error correction. Finally, it reconstructs LDPC parity-check matrix effectively by making comprehensive use of parity-check vector solution, error code elimination, parity-check matrix sparsity and LDPC codes decoding to iterate. Simulation results show that, for the (576, 288) LDPC codes in IEEE 802. 16e standard, the proposed algorithm can provide good performance even when the bit error rate is 0. 0022.

Key words: channel coding, LDPC codes, blind recognition, parity-check vector, sparse, open set recognition, bit error rate