A general analytical framework based on generalized mutual information is applied to the analysis of massive multiple-input-multiple-output systems with low-resolution output quantization. For Gaussian codebook ensemble and nearestneighbor decoding rule, an equivalence relationship is established for general nonlinear transceiver distortion, that the effective signal-to-noise ratio based on the generalized mutual information is consistent with the heuristically derived signal-to-quantizationnoise ratio based on Bussgang theorem. Specializing to lowresolution output quantization, an extensively used approximate model called the additive quantization noise model is shown to be inconsistent with the generalized mutual information analysis, but this inconsistency can be remedied by taking into account the correlation within the quantization noise vector.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    On Transmission Model for Massive MIMO under Low-Resolution Output Quantization


    Contributors:
    Li, Bin (author) / Liang, Ning (author) / Zhang, Wenyi (author)


    Publication date :

    2017-06-01


    Size :

    214689 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    CSI Quantization for FDD Massive MIMO Communication

    Vehkalahti, Roope / Liao, Jialing / Pllaha, Tefjol et al. | IEEE | 2021



    Adaptive DNN-based CSI Feedback with Quantization for FDD Massive MIMO Systems

    Gao, Junjie / Bouazizi, Mondher / Ohtsuki, Tomoaki et al. | IEEE | 2022


    Geometrical Model for Massive MIMO Systems

    Cheng, Xudong / He, Yejun | IEEE | 2017