National Taiwan University
To date there is no practical means to evaluate the true Word Error Probability (WEP) of a given turbo or LDPC code because typical decoders cannot achieve the performance of ML decoding. In this paper, the authors propose a viable methodology to establish tight bounds on the ML-decoding WEP for these codes through empirical simulation. Their framework centers on the efficient use of multiple-output decoding induced by receiver-generated side information, or gift. At low WEP regime, perturbed decoding can give tight bounds. In high WEP regime, due to the prohibitive complexity of perturbed decoding, they instead pursue other type of gifts.