Channel Detection in Coded Communication - Weinberger, Nir; Merhav, Neri (IEEE transactions on information theory, 2017)
The problem of block-coded communication where in each block the channel law belongs to one of two disjoint sets is considered. The decoder is aimed to decode only messages that have undergone a channel from one of the sets, and thus has to detect the set which contains the underlying channel. The simplified case where each of the sets is a singleton is studied first. The decoding error, false alarm, and misdetection probabilities of a given code are defined, and the optimum detection/decoding rule in a generalized Neyman-Pearson sense is derived. Sub-optimal detection/decoding rules are also introduced which are simpler to implement. Then, various achievable bounds on the error exponents are derived, including the exact single-letter characterization of the random coding exponents for the optimal detector/decoder. The random coding analysis is then extended to general sets of channels, and an asymptotically optimal detector/decoder under a worst case formulation of the error probabilities is derived, as well as its random coding exponents. The case of a pair of binary symmetric channels is discussed in detail.