Lossless coding for distributed streaming sources

Distributed source coding is traditionally viewed in the block coding context -- all the source symbols are known in advance at the encoders. This paper instead considers a streaming setting in which iid source symbol pairs are revealed to the separate encoders in real time and need to be reconstructed at the decoder with some tolerable end-to-end delay using finite rate noiseless channels. A sequential random binning argument is used to derive a lower bound on the error exponent with delay and show that both ML decoding and universal decoding achieve the same positive error exponents inside the traditional Slepian-Wolf rate region. The error events are different from the block-coding error events and give rise to slightly different exponents. Because the sequential random binning scheme is also universal over delays, the resulting code eventually

• Type: Journal
• Year: 2006
• Where: CORR
• Authors: Cheng Chang, Stark C. Draper, Anant Sahai
• Keywords: CORR 2006, Education, Error Exponents, Sequential Random Binning, Source Symbol