Abstract
In this thesis, we applied dynamic scheduling of silent variable nodes free residual belief propagation (SVNF-RBP) to low-density parity-check convolutional codes (LDPC-CCs). Informed dynamic scheduling (IDS) can get higher convergenence speed and better performance by updating message efficiently rather than standard sequential scheduling, this is the main reason why we use IDS. We choose SVNF-RBP to be core algorithm in all types of IDS, because SVNF-RBP has an algorithm behavior which can assign variable node sequentially, this character makes SVNF-RBP combined with LDPC-CCs easily, and makes iteration-parallel decoding of LDPC-CCs still function work. Because SVNF-RBP overcame two phenomenon of greedy group and silent variable nodes, so the performance and the convergenence speed of SVNF-RBP will be better than the performance and the convergenence speed of traditional IDS. Finally, we achieved incremental redundancy (IR) typed hybrid automatic repeat request (HARQ) by designing IEEE 802.16m puccturing pattern.