Information Theory: Coding Theorems for Discrete Memoryless Systems
Information Theory: Coding Theorems for Discrete Memoryless Systems
A Neyman-Pearson approach to universal erasure and list decoding
IEEE Transactions on Information Theory
Capacity and Random-Coding Exponents for Channel Coding With Side Information
IEEE Transactions on Information Theory
Hi-index | 754.84 |
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, a universally achievable region of error exponents is 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 parameters to allow variable size list decoding. This extension gives a unified treatment for erasure/list decoding. An achievable region of exponential bounds on the probability of list error and the average number of incorrect messages on the list are given. Relations to Forney's and Csiszár and Körner's decoders for discrete memoryless channel are discussed. These results are obtained by exploring a random binning code with conditionally constant composition codewords proposed by Moulin and Wang, but with a different decoding rule and a modified analysis.