Queue based compression in a two-way relay network

Ertugrul Necdet Ciftcioglu, Yalin Evren Sagduyu, Aylin Yener, Randall A. Berry

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    4 Scopus citations

    Abstract

    We consider the problem of joint rate scheduling and lossy data compression in a two-way relay network with distortion-sensitive stochastic packet traffic. A relay node facilitates exchanging packets between the two sources. Network coding at the relay improves energy efficiency at the expense of additional packet delay. In addition, network coding couples the source queues through the distortion levels of their individual packet traffic. This fact motivates having each source adapt the transmission rate and the compression ratio jointly. We first formulate a centralized dynamic scheme for scheduling and compression with the objective of minimizing the energy consumption at the relay while satisfying stability and average distortion constraints. Lyapunov stability arguments are used to define a centralized policy based on the instantaneous queue backlogs and distortion levels. In addition, a decentralized algorithm is proposed where sources have limited (1-bit) information about each other's queue backlog and distortion levels. Numerical results demonstrate that the performance of the proposed decentralized algorithm approaches the energy-delay tradeoffs resulting from the centralized solution.

    Original languageEnglish (US)
    Title of host publication2010 44th Annual Conference on Information Sciences and Systems, CISS 2010
    DOIs
    StatePublished - Jun 24 2010
    Event44th Annual Conference on Information Sciences and Systems, CISS 2010 - Princeton, NJ, United States
    Duration: Mar 17 2010Mar 19 2010

    Publication series

    Name2010 44th Annual Conference on Information Sciences and Systems, CISS 2010

    Other

    Other44th Annual Conference on Information Sciences and Systems, CISS 2010
    CountryUnited States
    CityPrinceton, NJ
    Period3/17/103/19/10

    All Science Journal Classification (ASJC) codes

    • Information Systems
    • Information Systems and Management

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