Tightened Upper Bounds on the ML Decoding Error Probability of Binary Linear Block Codes

摘要

The performance of maximum-likelihood (ML) decoded binary linear block codesis addressed via the derivation of tightened upper bounds on their decodingerror probability. The upper bounds on the block and bit error probabilitiesare valid for any memoryless, binary-input and output-symmetric communicationchannel, and their effectiveness is exemplified for various ensembles ofturbo-like codes over the AWGN channel. An expurgation of the distance spectrumof binary linear block codes further tightens the resulting upper bounds.