基于因子图的Turbo码译码

Turbo码和LDPC码都可以实现接近Shannon理论极限的性能，Turbo码由于成员RSC码所固有的移位寄存器特性使得其编码较为容易实现，而对于接近Shannon容量的LDPC码，则需要大量的矩阵乘法运算才能完成信息的编码，电路实现较为复杂，另一方面，采用和积算法的LDPC码的译码过程则比采用BCJR算法（及其简化形式）的Turbo译码更加容易实现，且计算复杂度更低，将Turbo编码与LDPC码的译码相结合，对Turbo采用基于其因子图表示的和积译码算法进行译码，可以在很大程度上降低Turbo码的译码复杂度，并对交织器的设计及成员码的选择有一定的指导作用，仿真结果证明了该方案的有效性。

Factor Graphs Based Turbo Codes Decoding

Beth turbo codes and LDPC codes can achieve the Shannon limited performance. The constituent RSC codes in turbo codes are more structural and this lends the encoding problem easier with shift_register circuit.While the encoding of LDPC codes is performed via matrix multiplication, it is more complex than it appears for capacity_approaching LDPC codes. On the other hand,the soft_input soft_output BCJR algorithm,or the sub_optimal version of it,used for turbo_decoding is rather complex while sum_product algorithm used for LDPC decoding lends itself to parallel implementation and is computationally simpler. Combining the turbo codes encoding and LDPC decoding,a new scheme based on factor graphs and sum_product algorithm is developed, Which can reduce the decoding complexity of turbo codes greatly,and also has some guides in the designing of interleaver and the choosing of RSC constituent codes. Simulation shows the correctness of the scheme.