Beamspace channel estimation for 3D lens-based millimeter-wave massive MIMO systems

Xinyu Gao, Linglong Dai, Shuangfeng Han, I. Chih-Lin, Fumiyuki Adachi

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    15 Citations (Scopus)

    Abstract

    Lens-based mmWave massive MIMO can significantly reduce the number of required RF chains without obvious performance loss, where the accurate information of beamspace channel is required. However, existing beamspace channel estimation schemes are based on the 2D beamspace channel model. In this paper, we consider the more general 3D beamspace channel model, and propose an adaptive support detection (ASD)-based channel estimation scheme. The basic idea is to decompose the 3D beamspace channel estimation problem into several sub-problems, and each one only deals with a sparse channel component. For each channel component, we first adaptively detect its support with high accuracy by exploiting the horizontal and vertical sparsity of 3D beamspace channel. Then, we remove the influence of this channel component to detect the support of the next channel component. After the support detections of all channel components, we can estimate the nonzero elements of the beamspace channel with low pilot overhead. Simulation results verify that the proposed scheme enjoys satisfying accuracy, even with low SNR.

    Original languageEnglish
    Title of host publication2016 8th International Conference on Wireless Communications and Signal Processing, WCSP 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781509028603
    DOIs
    Publication statusPublished - 2016 Nov 21
    Event8th International Conference on Wireless Communications and Signal Processing, WCSP 2016 - Yangzhou, China
    Duration: 2016 Oct 132016 Oct 15

    Publication series

    Name2016 8th International Conference on Wireless Communications and Signal Processing, WCSP 2016

    Other

    Other8th International Conference on Wireless Communications and Signal Processing, WCSP 2016
    Country/TerritoryChina
    CityYangzhou
    Period16/10/1316/10/15

    ASJC Scopus subject areas

    • Signal Processing
    • Computer Networks and Communications

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