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

The performance of maximum-likelihood (ML) decoded binary linear block codes is addressed via the derivation of tightened upper bounds on their decoding error probability. The upper bounds on the block and bit error probabilities are valid for any memoryless, binary-input and output-symmetric communication channel. The effectiveness of these bounds is exemplified for ensembles of turbo-like codes.