Research on Decoding Algorithm for LDPC Codes
|School||Harbin Institute of Technology|
|Course||Information and Communication Engineering|
|Keywords||LDPC codes parity check matrix BP Algorithm bipartite graph|
As the need for wireless data and multimedia services, the future mobile communication system must achieve the data transmission with high data rate. So it is very important to ensure the reliability of data communication. The channel coding theory is a hot research on communication system, and one of them is Low-density-parity-check codes (LDPC). LDPC codes first discovered by Gallager in 1962 are a class of linear block error-correcting codes that can be defined by the very sparse parity-check matrix or the bipartite graph. They have very attractive properties: error performance approaching Shannon limits, easy description and implementation, convenient theoretical analysis and research, easily decoded in complete parallel ways and suitable for hardware implementation. In resent years, LDPC codes have gained increasingly consideration of researchers with their excellent error performance, simple description and very good application foreground.In this thesis first channel coding and the basic theory of LDPC codes are introduced, and then the decoding algorithm of LDPC codes are studied in-depth. On the basis of introducing the probability domain BP algorithm and the LLR BP algorithm, the research focuses on the improved BP decoding algorithm for the LDPC codes, including UMP_BP algorithm, Normalized UMP_BP algorithm and Offset UMP_BP algorithm. Comparing with the BP decoding algorithm, UMP_BP algorithm reduces the decoding complexity, but meanwhile loses a part of performance. Based on the situation, Normalized UMP_BP algorithm and Offset UMP_BP algorithm are put forward. The two algorithms improve the decoding performance and reduce the decoding complexity as the same as UMP_BP algorithm. At last, through simulation for various decoding algorithms’performance, the results prove the excellent performance of the improved decoding algorithm, and the theoretical foundation is prepared to practical application by research.