Efficient Maximum-Likelihood Soft-Decision Decoding of Linear Block Codes Using Algorithm A

In this report we present a novel and efficient maximum-likelihood soft-decision decoding algorithm for linear block codes. The approach used here is to convert the decoding problem into a search problem through a graph which is a trellis for an equivalent code of the transmitted code. Algorithm A*, which uses a priority-first search strategy, is employed to search through this graph. This search is guided by an evaluation function f defined to take advantage of the information provided by the received vector and the inherent properties of the transmitted code. This function f is used to drastically reduce the search space and to make the decoding efforts of this decoding algorithm adaptable to the noise level. Simulation results for the {48, 24) and the {72, 36) binary extended quadratic residue codes and the (128, 64) binary extended BCH code are given to substantiate the above claim.