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    A compressive sensing based iterative algorithm for channel and impulsive noise estimation in underwater acoustic OFDM systems

    Access Status
    Fulltext not available
    Authors
    Zhang, J.
    He, Z.
    Chen, Jaden
    Rong, Yue
    Date
    2017
    Type
    Conference Paper
    
    Metadata
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    Citation
    Zhang, J. and He, Z. and Chen, J. and Rong, Y. 2017. A compressive sensing based iterative algorithm for channel and impulsive noise estimation in underwater acoustic OFDM systems, Oceans 2017.
    Source Title
    OCEANS 2017 - Anchorage
    Source Conference
    Oceans 2017
    ISBN
    9780692946909
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    URI
    http://hdl.handle.net/20.500.11937/68609
    Collection
    • Curtin Research Publications
    Abstract

    © 2017 Marine Technology Society. Underwater acoustic (UA) channel is often affected by strong impulsive noise. In this paper, a compressive sensing based iterative algorithm is proposed to accurately estimate the channel state information and mitigate the impulsive noise, which is important to ensure high-speed data transmission in UA orthogonal frequency-division multiplexing communication systems. By exploiting the sparsity of the impulsive noise and channel impulse response in the time domain, we adopt the orthogonal matching pursuit algorithm to improve the accuracy of channel estimation with relatively low computational complexity. The proposed algorithm is evaluated through numerical simulations and real data collected during a UA communication experiment conducted in December 2015 in the estuary of the Swan River, Western Australia. The results show that the proposed algorithm has a better performance than existing approaches.

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