Modified multiple stack algorithm for decoding convolutional codes

The multiple stack algorithm (MSA), devised by Chevillat and Costello (1977), is an efficient long the MSA, substack size and the number of transferred survivors (or successors) are assumed to be small. Lower error probabilities can be achieved by increasing the first stack size and/or increasing the computational limit. A large storage capacity for survivors is required to prevent memory overflow and achieve a low error probability. The authors present a modified MSA, in which the storage capacity for survivors is kept constant, while the substacks are arranged in a ring-like structure to handle the overflow problem of storage for survivors. In addition, the substack size and the number of transferred survivors are made large to improve the performance. The performance of the modified MSA in decoding a convolutional code with constraint length m=23 is investigated and compared with the performance of the unmodified MSA