High-performance soft decision decoding method using table-aided algorithm for block code

Abstract

Although various methods exist in soft decision decoding methods for block codes, of those that can be applied to linear and nonlinear coding, there are not many with low levels of computation that provide high levels of performance. In this paper, a method is proposed that reduces computation requirements while maintaining performance close to that of maximum likelihood decoding by a decision-making procedure in which a candidate codeword table is referenced by performing Euclidean distance comparisons on the received signal's hard decision binary sequence. The computation requirements and the block error rate performance are investigated through computer simulation to demonstrate the effectiveness of the proposed method in nonlinear β codes in additive Gaussian noise channels and fading channels. These results show that the block error rate performance of the proposed method in the additive Gaussian noise channel is about the same as the performance of the Chase 11 algorithm and is only slightly inferior to that of maximum likelihood decoding. Concerning the amount of computations, it is possible to reduce the complexity down to about 1% of that required by maximum likelihood decoding, and also the complexity can be reduced below that of the Chase II algorithm. On the other hand, in the fading channel, the block error rate performance of the proposed method, when compared to maximum likelihood decoding performance, reveals a decrease in Eb/N0 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. © 1997 Scripta Technica, Inc. Electron Comm Jpn Pt 1, 80(9): 56–67, 1997