Majority-logic-like vector symbol decoding with alternative symbol value lists

Abstract

Majority-logic-like decoding is an outer concatenated code decoding technique using the structure of a binary majority logic code. It is shown that it is easy to adapt such a technique to handle the case where the decoder is given an ordered list of two or more prospective candidates for each inner code symbol. Large reductions in failure probability can be achieved. Simulation results are shown for both block and convolutional codes. Punctured convolutional codes allow a convenient flexibility of rate while retaining high decoding power. For example, a (856, 500) terminated convolutional code with an average of 180 random first-choice symbol errors can correct all the errors in a simple manner about 97% of the time, with the aid of second-choice values. A (856, 500) maximum-distance block code could correct only up to 178 errors based on guaranteed correction capability and would be extremely complex.