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IEEE International Symposium on Information Theory (ISIT)

When is hard decision decoding enough?

Peter F. Swaszek

Published Nov 19, 2002• 0 citations
Publisher

Abstract

Many algorithms for soft and near-soft decision decoding of block codes start by implementing hard decision decoding. In several instances it has been noted that simple tests of the hard decision result may allow the algorithm to terminate at this point. This paper explores this notion in detail.
DOI
10.1109/isit.1995.531156

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In many modern communication systems, the full benefits of error-correction coding are only realised if the decoder is able to utilise soft decision decoding. In this chapter, we give both approximate and exact bounds on the performance of soft decision decoding compared to hard decision decoding. The effects of soft decision quantisation are explored as a function of the number of quantisation levels. Examples are given of the different performance achieved using soft and quantised soft decision decoding for (100,50) and (200,100) binary codes. A modified version of the near maximum likelihood decoder, the Dorsch decoder described in Chap. 15 , is presented for hard decision decoding. The performance improvements achieved by the decoder, compared to bounded distance decoding, are evaluated for some BCH codes. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
In this paper,the ChaseⅡ algorithm,which is well known as a reliability-based decoding algorithm,is used for the soft decoding of the(23,12,7)Golay code.This soft-decision decoding algorithm improves greatly the error-correcting capacity compared with algebraic hard-decision decoding algorithms,but also results in more computational complexity.To overcome this,a optimality condition is introduced to quickly terminate the ChaseⅡ decoding process.Computer simulation results got by VC6.0 show that soft decoding obtains 1.7 dB coding gain compared with hard decoding case at BER of 10-5,and the modified chase-II algorithm based on the optimality condition reduces the total simulation time by 87.64%,and thus improves greatly the decoding efficiency.