IRWIN AND JOAN JACOBS CENTER FOR COMMUNICATION AND INFORMATION TECHNOLOGIES Erasure/List Exponents for Slepian-Wolf Decoding

IRWIN AND JOAN JACOBS CENTER FOR COMMUNICATION AND INFORMATION TECHNOLOGIES Erasure/List Random Coding Error Exponents Are Not Universally Achievable

IRWIN AND JOAN JACOBS CENTER FOR COMMUNICATION AND INFORMATION TECHNOLOGIES Achievable Error Exponents for Channel with Side Information ― Erasure and List Decoding

We consider a decoder with an erasure option and a variable size list decoder for channels with non-casual side information at the transmitter. First, universally achievable error exponents are offered for decoding with an erasure option using a parameterized decoder in the spirit of Csiszár and Körner’s decoder. Then, the proposed decoding rule is generalized by extending the range of its para...

IRWIN AND JOAN JACOBS CENTER FOR COMMUNICATION AND INFORMATION TECHNOLOGIES Simplified Erasure/List Decoding

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 fu...

IRWIN AND JOAN JACOBS CENTER FOR COMMUNICATION AND INFORMATION TECHNOLOGIES Statistical Physics of Random Binning

We consider the model of random binning and finite–temperature decoding for Slepian–Wolf codes, from a statistical–mechanical perspective. While ordinary random channel coding is intimately related to the random energy model (REM) – a statistical–mechanical model of disordered magnetic materials, it turns out that random binning (for Slepian–Wolf coding) is analogous to another, related statist...

IRWIN AND JOAN JACOBS CENTER FOR COMMUNICATION AND INFORMATION TECHNOLOGIES Universal Decoding for Source–Channel Coding with Side Information

We consider a setting of Slepian–Wolf coding, where the random bin of the source vector undergoes channel coding, and then decoded at the receiver, based on additional side information, correlated to the source. For a given distribution of the randomly selected channel codewords, we propose a universal decoder that depends on the statistics of neither the correlated sources nor the channel, ass...