Distributed power allocation strategies for parallel relay networks

Min Chen, Semih Serbetli, Aylin Yener

    Research output: Contribution to journalArticlepeer-review

    120 Scopus citations

    Abstract

    We consider a source-destination pair assisted by parallel regenerative decode-and-forward relays operating in orthogonal channels. We investigate distributed power allocation strategies for this system with limited channel state information at the source and the relay nodes. We first propose a distributed decision mechanism for each relay to individually make its decision on whether to forward the source data. The decision mechanism calls for each relay that is able to decode the information from the source to compare its relay-to-destination channel gain with a given threshold. We identify the optimum distributed power allocation strategy that minimizes the total transmit power while providing a target signal-to-noise ratio at the destination with a target outage probability. The strategy dictates the optimum choices for the source power as well as the threshold value at the relays. Next, we consider two simpler distributed power allocation strategies, namely the passive source model where the source power and the relay threshold are fixed, and the single relay model where only one relay is allowed to forward the source data. These models are motivated by limitations on the available channel state information as well as ease of implementation as compared to the optimum distributed strategy. Simulation results are presented to demonstrate the performance of the proposed distributed power allocation schemes. Specifically, we observe significant power savings with proposed methods as compared to random relay selection.

    Original languageEnglish (US)
    Article number4450823
    Pages (from-to)552-561
    Number of pages10
    JournalIEEE Transactions on Wireless Communications
    Volume7
    Issue number2
    DOIs
    StatePublished - Feb 2008

    All Science Journal Classification (ASJC) codes

    • Computer Science Applications
    • Electrical and Electronic Engineering
    • Applied Mathematics

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