Sequential decoding of convolutional codes by a compressed multiple queue algorithm

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The conventional multiple stack algorithm (MSA) is an-efficient approach for solving erasure problems in sequential decoding. However, the requirements of multiple stacks and large memory make its implementation difficult. Furthermore,the MSA allows only one stack to be in use at a time: the ether stacks will stay idle until the process in that stack is terminated. Thus it seems difficult to implement the MSA with parallel processing technology. A two-stack scheme is proposed to achieve similar effects to the MSA. The scheme greatly reduces the loading for data transfer and I/O complexity required in the MSA, and makes parallel processing possible. An erasure-free sequential decoding algorithm for convolutional codes, the compressed multiple-queue algorithm (CMQA), is introduced, based on systolic priority queue technology, which-can reorder the path metrics in a short and constant time. The decoding speed will therefore be much faster than in traditional sequential decoders using sorting methods. In the CMQA, a systolic priority queue is divided into two queues by adding control signals, thereby simplifying implementation. Computer simulations show that the CMQA outperforms the MSA in bit error rate, with about one-third the memory requirement of the MSA.