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    Compressed sensing techniques for receiver based post-compensation of transmitter's nonlinear distortions in OFDM systems

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    Type
    Article
    Authors
    Owodunni, Damilola S.
    Ali, Anum Z.
    Quadeer, Ahmed Abdul
    Al-Safadi, Ebrahim B.
    Hammi, Oualid
    Al-Naffouri, Tareq Y. cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2014-04
    Permanent link to this record
    http://hdl.handle.net/10754/563463
    
    Metadata
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    Abstract
    In this paper, compressed sensing techniques are proposed to linearize commercial power amplifiers driven by orthogonal frequency division multiplexing signals. The nonlinear distortion is considered as a sparse phenomenon in the time-domain, and three compressed sensing based algorithms are presented to estimate and compensate for these distortions at the receiver using a few and, at times, even no frequency-domain free carriers (i.e. pilot carriers). The first technique is a conventional compressed sensing approach, while the second incorporates a priori information about the distortions to enhance the estimation. Finally, the third technique involves an iterative data-aided algorithm that does not require any pilot carriers and hence allows the system to work at maximum bandwidth efficiency. The performances of all the proposed techniques are evaluated on a commercial power amplifier and compared. The error vector magnitude and symbol error rate results show the ability of compressed sensing to compensate for the amplifier's nonlinear distortions. © 2013 Elsevier B.V.
    Citation
    Owodunni, D. S., Ali, A., Quadeer, A. A., Al-Safadi, E. B., Hammi, O., & Al-Naffouri, T. Y. (2014). Compressed sensing techniques for receiver based post-compensation of transmitter’s nonlinear distortions in OFDM systems. Signal Processing, 97, 282–293. doi:10.1016/j.sigpro.2013.10.029
    Sponsors
    This work was supported by King Abdulaziz City for Science and Technology (KACST) through the Science & Technology Unit at King Fahd University of Petroleum & Minerals through Project no. 11-ELE1651-04 as part of the National Science, Technology and Innovation Plan.
    Publisher
    Elsevier BV
    Journal
    Signal Processing
    DOI
    10.1016/j.sigpro.2013.10.029
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.sigpro.2013.10.029
    Scopus Count
    Collections
    Articles; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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