Parallel iterative decoding for orthogonal convolutional codes

A parallel design for the iterative belief propagation decoding of convolutional self-orthogonal codes is presented. This parallel structure allows a substantial increase in the speed of iterative decoding, approaching that of one-step decoding at the cost of only a negligible degradation of coding gain. Together with its low encoding complexity, this coding scheme may be especially attractive for very high data rate applications. The parallel structure can also be generalized to the iterative threshold decoding of convolutional self doubly orthogonal codes, providing a more flexible tradeoff between decoding speed and error performance.