A New decoding Algorithm for Maximum Likelihood Decoding of Linear Block Codes

Abstract

Several researchers have presented techniques for decoding linear block codes that convert the decoding problem into a problem of graph search on a trellis derived from the generator or the paritycheck matrices of the code. In this paper, we propose a new method for reducing the time complexity and the space complexity of the A search method for maximum likelihood decoding of linear block codes.
Our method utilizes the local descriptions of the minimal trellis of the code. The proposed method has
been tested on the AWGN channel and the simulation results has shown the high efficiency of the proposed method, as compared to the A search method, while maintaining the same probability of decoding error.