Research On Optimized Algorithms Of Bipartite Graph For LDPC Codes

Low-density parity-check codes (LDPC) in graphical models come to be one of the best coding technologies because of their low-complicity iterative decoding algorithm and capacity approaching performance, and they attract more and more researchers'eyes in recent years. The construction of bipartite graph plays an important part in the LDPC code. The performance of low-density parity-check codes can be improved by optimizing the Tanner graph.In this dissertation, the basic principles of the coding and decoding of LDPC codes are studied systematically. A new edge growth with depth constraints algorithm for constructing Tanner graph of LDPC codes is proposed. The main results and contents are as follows.1. The principles of coding and decoding for low-density parity-check codes are briefly summarized, the main factors which can impact the performance of LDPC codes such as degree sequence, cycles and connectivity of Tanner graph are systematically analyzed, emphasis on the connectivity.2. Several optimized algorithms for constructing Tanner graph of LDPC codes such as cycles eliminating algorithms and connectivity improving algorithms are addressed. The simulation results show that the codes constructed with these algorithms has lower error floor. The graph of simulation performance is presented. Besides, the performance of the codes constructed with these algorithms is analyzed.3. A new edge growth with depth constraints algorithm for constructing Tanner graph of LDPC codes is proposed. The performance of LDPC codes constructed with the new algorithm is better.