Study Of Averaged Iterative Decoding Algorithm

Low-Density Parity-Check(LDPC) codes are a class of capacity approaching error-correcting codes.By using low complexity algorithms based on belief propagation,LDPC codes can get near Shannon limit decoding performance. For long code lengths,LDPC codes can even outperform Turbo codes. Low-density parity check (LDPC) codes are known to perform very well under iterative decoding. Due to the advantages of LDPC codes,their applications in reliable communication have become one of the most attractive field in channal coding community. However,those codes often exhibit an error floor phenomenon in the high signal-to-noise(SNR) region.Multi-edge type LDPC codes yields improvements in performance,range of applications, adaptability and error floor.Based on the comprehension of iterative decoding algorithm and Multi-edge type LDPC codes ,this thesis analyses the averaged iterative decoding algorithm,which can reduce the error floor of LDPC codes.The main results and contents are as follows.1.Channel decoding,linear codes LDPC codes and Multi-edge type LDPC codes are adressed.Trapping sets and error floor phenomenon are analyzed and the methods of reduce the error floor of LDPC codes is introduced.2.Iterrative decoding about LDPC codes is studied,especially averaged iterative algorithm,and such algorithm for Multi-edge type LDPC codes is proposed,which can reduce the error floor of Multi-edge type LDPC codes.