Detection of Large-Scale Wireless Systems via Sparse Error Recovery

Jun Won Choi, Byonghyo Shim

    Research output: Contribution to journalArticlepeer-review

    12 Citations (Scopus)

    Abstract

    In this paper, we propose a new detection algorithm for large-scale wireless systems, referred to as post sparse error detection (PSED) algorithm, that employs a sparse error recovery algorithm to refine the estimate of a symbol vector obtained by the conventional linear detector. The PSED algorithm operates in two steps: First, sparse transformation converting the original nonsparse system into the sparse system whose input is an error vector caused by the symbol slicing; and second, the estimation of the error vector using the sparse recovery algorithm. From the asymptotic mean square error analysis and empirical simulations performed on large-scale wireless systems, we show that the PSED algorithm brings significant performance gain over classical linear detectors while imposing relatively small computational overhead.

    Original languageEnglish
    Article number8025598
    Pages (from-to)6038-6052
    Number of pages15
    JournalIEEE Transactions on Signal Processing
    Volume65
    Issue number22
    DOIs
    Publication statusPublished - 2017 Nov 15

    Bibliographical note

    Publisher Copyright:
    © 2017 IEEE.

    Keywords

    • Sparse signal recovery
    • compressive sensing
    • error correction
    • large-scale systems
    • linear minimum mean square error
    • orthogonal matching pursuit
    • sparse transformation

    ASJC Scopus subject areas

    • Signal Processing
    • Electrical and Electronic Engineering

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