Information Spectrum Approach to the Source Channel Separation Theorem (1306.6288v1)

Abstract: A source-channel separation theorem for a general channel has recently been shown by Aggrawal et. al. This theorem states that if there exist a coding scheme that achieves a maximum distortion level d_{max} over a general channel W, then reliable communication can be accomplished over this channel at rates less then R(d_{max}), where R(.) is the rate distortion function of the source. The source, however, is essentially constrained to be discrete and memoryless (DMS). In this work we prove a stronger claim where the source is general, satisfying only a "sphere packing optimality" feature, and the channel is completely general. Furthermore, we show that if the channel satisfies the strong converse property as define by Han & verdu, then the same statement can be made with d_{avg}, the average distortion level, replacing d_{max}. Unlike the proofs there, we use information spectrum methods to prove the statements and the results can be quite easily extended to other situations.