Multiuser detection via compressive sensing

Byonghyo Shim*, Byungkwen Song

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    122 Citations (Scopus)

    Abstract

    In this paper, we consider a multiuser detection technique when the signal sparsity is changing over time. The key ingredient of our method is a clever switching between the CS reconstruction algorithm and classical detection depending on the sparsity level of the signals being detected. Since none of these approaches is uniformly better in a situation where the sparsity level is varying, proposed switching algorithm can effectively combine the merits of both. We show that the proposed switching algorithm provides substantial performance gain over individual algorithms in the multiuser detection of CDMA downlink.

    Original languageEnglish
    Article number6196146
    Pages (from-to)972-974
    Number of pages3
    JournalIEEE Communications Letters
    Volume16
    Issue number7
    DOIs
    Publication statusPublished - 2012

    Bibliographical note

    Funding Information:
    Manuscript received September 22, 2011. The associate editor coordinating the review of this letter and approving it for publication was P. Cotae. B. Shim is with the School of Information and Communication, Korea University, Seoul, Korea, 136-701 (e-mail: [email protected]). B. Song is with the Department of Electronics Engineering, Seokyeong University, Seoul, Korea, 136-704 (e-mail: [email protected]). This research was supported by the research grant of Seokyeong University (2009) and the Basic Science Research Program through the National Research Foundation (NRF) funded by the Ministry of Education, Science and Technology (MEST) (No. 2011-0012525) and second Brain Korea 21 project. Digital Object Identifier 10.1109/LCOMM.2012.050112.111980

    Keywords

    • Compressive sensing
    • multiuser detection
    • orthogonal matching pursuit
    • sparsity

    ASJC Scopus subject areas

    • Modelling and Simulation
    • Computer Science Applications
    • Electrical and Electronic Engineering

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