HIGH-PERFORMANCE SOFT DECISION DECODING METHOD USING TABLE-AIDED ALGORITHM FOR BLOCK CODE

Although various methods exist in soft decision decoding methods for b lock codes, of those that can be applied to linear and nonlinear codin g, there are not many with low levels of computation that provide high levels of performance. In this paper, a method is proposed that reduc es computation requirements while maintaining performance close to tha t of maximum likelihood decoding by a decision-making procedure in whi ch a candidate codeword table is referenced by performing Euclidean di stance comparisons on the received signal's hard decision binary seque nce. The computation requirements and the block error rate performance are investigated through computer simulation to demonstrate the effec tiveness of the proposed method in nonlinear beta codes in additive Ga ussian noise channels and fading channels. These results show that the block error rate performance of the proposed method in the additive G aussian noise channel is about the same as the performance of the Chas e II algorithm and is only slightly inferior to that of maximum likeli hood decoding. Concerning the amount of computations, it is possible t o reduce the complexity down to about 1% of that required by maximum l ikelihood decoding, and also the complexity can be reduced below that of the Chase II algorithm. On the other hand, in the fading channel, t he block error rate performance of the proposed method, when compared to maximum likelihood decoding performance, reveals a decrease in E-b/ N-0 of about 1 dB, and it is seen to have good performance compared to the Chase II algorithm. Also, application toward quasi-cyclic coding/ 4-ary ASK coding using a candidate word table with respect to a 4-ary sequence applied with BCH coding is investigated, and superior results are obtained. (C) 1997 Scripta Technica, Inc.