The Improved Algorithm Based On BP Decoding Algorithm Of LDPC Codes

With the development of the times, communication has been playing a more and more important role in people’s daily life. As a class of error correcting codes which have capacity-approaching performance and relatively low decoding complexity, Low Density Parity-Check Codes(LDPC) has become a strong competitor to Turbo codes, and has become a good candidate for future communication systems.Among all decoding algorithms for LDPC codes, BP algorithm is the most popular one. The BP algorithm are able to achieve performance very close to the channel capacity in AWGN environment both in theory and in practice. Although the BP algorithm has many advantages, it still has a high complexity, we still need to improve its decoding efficiency. The complexity of BP algorithm is mainly reflected in the following two aspects: In each iteration, the BP algorithm need to calculate all of the bit information and the parity information, so, the amount of computation required for each iteration is the same. But with the number of iterations increases, less and less bits are corrected in each iteration; Besides, BP algorithm will iterate until either a valid code word has been found or the predefined maximum number of iterates has been reached before stopping, but after a few iterations, some bits which are not corrected decoding will not be corrected decoding in the subsequent iterations. In summary, although BP algorithm is good, there is still certainly room for improvement.Among many improved algorithm of BP algorithm, FC(Forced-convergence)algorithm aims at reducing complexity by decreasing the number of active nodes in every iteration. NSPC(Number of satisfied parity-check constraints)algorithm reduces the average number of decoding iterations by distinguishing the received block into decodable and undecodable. Because the performance of FC algorithm is not good, this paper made some improvement on the FC algorithm, then, upon the improved FC algorithm and NSPC algorithm, we present FCES algorithm, which can not only reduce the number of active nodes in each iteration like FC algorithm, but also can reduce the average number of iterations like NSPC algorithm, besides, the performance of FCES algorithm is better than FC algorithm and NSPC algorithm. Simulations and analysis indicate that compared with BP algorithm, FCES algorithm greatly reduces decoding complexity, improved coding efficiency and convergence speed in the case of minimal decoding performance loss.