Slepian-Wolf coding

Analysis of Slepian Wolf Coding

Universal Incremental Slepian-Wolf Coding

We present a strategy for Slepian-Wolf coding when the joint distribution of the sources is unknown. The encoders use an incremental transmission policy, and the decoder a universal sequential decision test. We show that the decoder is able to decode shortly after the rates of transmission exceed the Slepian-Wolf bounds. The decoder then send an ACK back to the encoders, terminating transmissio...

Polar Codes for Nonasymmetric Slepian-Wolf Coding

A method to construct nonasymmetric distributed source coding (DSC) scheme using polar codes which can achieve any point on the dominant face of the Slepian–Wolf (SW) rate region for sources with uniform marginals is considered. In addition to nonasymmetric case, we also discuss and show explicitly how asymmetric and single source compression is done using successive cancellation (SC) polar dec...

Toward constructive Slepian-Wolf coding schemes

This chapter deals with practical solutions for the Slepian Wolf (SW) coding problem, which refers to the problem of lossless compression of correlated sources with coders which do not communicate. Here, we will consider the case of two binary correlated sources X and Y , characterized by their joint distribution. If the two coders communicate, it is well known from Shannon’s theory that the mi...

Redundancy Rates of Slepian-Wolf Coding∗

The results of Shannon theory are asymptotic and do not reflect the finite codeword lengths used in practice. Recent progress in design of distributed source codes, along with the need for distributed compression in sensor networks, has made it crucial to understand how quickly distributed communication systems can approach their ultimate limits. Slepian and Wolf considered the distributed enco...