Simplified Erasure/List Decoding
Abstract
We consider the problem of erasure/list decoding using certain classes of simplified decoders. Specifically, we assume a class of erasure/list decoders, such that a codeword is in the list if its likelihood is larger than a threshold. This class of decoders both approximates the optimal decoder of Forney, and also includes the following simplified subclasses of decoding rules: The first is a function of the output vector only, but not the codebook (which is most suitable for high rates), and the second is a scaled version of the maximum likelihood decoder (which is most suitable for low rates). We provide single-letter expressions for the exact random coding exponents of any decoder in these classes, operating over a discrete memoryless channel. For each class of decoders, we find the optimal decoder within the class, in the sense that it maximizes the erasure/list exponent, under a given constraint on the error exponent. We establish the optimality of the simplified decoders of the first and second kind for low and high rates, respectively.
Cite
@article{arxiv.1412.1964,
title = {Simplified Erasure/List Decoding},
author = {Nir Weinberger and Neri Merhav},
journal= {arXiv preprint arXiv:1412.1964},
year = {2016}
}
Comments
Submitted to IEEE Transactions on Information Theory