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    Optimum M-PAM Transmission for Massive MIMO Systems with Channel Uncertainty

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    Type
    Preprint
    Authors
    Alrashdi, Ayed cc
    Kammoun, Abla cc
    Muqaibel, Ali H.
    Al-Naffouri, Tareq Y. cc
    KAUST Department
    Electrical Engineering Program
    Electrical Engineering
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2020-08-16
    Permanent link to this record
    http://hdl.handle.net/10754/664793
    
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    Abstract
    This paper considers the problem of symbol detection in massive multiple-input multiple-output (MIMO) wireless communication systems. We consider hard-thresholding preceeded by two variants of the regularized least squares (RLS) decoder; namely the unconstrained RLS and the RLS with box constraint. For all schemes, we focus on the evaluation of the mean squared error (MSE) and the symbol error probability (SEP) for M-ary pulse amplitude modulation (M-PAM) symbols transmitted over a massive MIMO system when the channel is estimated using linear minimum mean squared error (LMMSE) estimator. Under such circumstances, the channel estimation error is Gaussian which allows for the use of the convex Gaussian min-max theorem (CGMT) to derive asymptotic approximations for the MSE and SER when the system dimensions and the coherence duration grow large with the same pace. The obtained expressions are then leveraged to derive the optimal power distribution between pilot and data under a total transmit energy constraint. In addition, we derive an asymptotic approximation of the goodput for all schemes which is then used to jointly optimize the number of training symbols and their associated power. Numerical results are presented to support the accuracy of the theoretical results.
    Publisher
    arXiv
    arXiv
    2008.06993
    Additional Links
    https://arxiv.org/pdf/2008.06993
    Collections
    Preprints; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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