In millimeter-wave (mmWave) communication, accurate acquisition of channel state information is vital in enabling reliable beamforming transmission of multiple data-streams in both single-user and multi-user scenarios. Previously, compressive sensing (CS) techniques have been widely exploited for channel estimation purpose, thanks to the sparse nature of mmWave channels. However, most of CS schemes are non-adaptive and show poor estimation performance when the signal-to-noise ratio is low. Enhanced CS-based schemes, such as multi-stage adaptive CS scheme have also been proposed, yet the achievable performance is still unsatisfactory under multi-path environments. In this paper, we advance the existing studies and propose an improved two-stage adaptive channel estimation (TSACE) scheme. In the first stage, a certain number of random sensing measurements are performed over the entire space. Given the initial measurements, the posterior probability distribution of possible combinations of angular supports for the sparse channel are computed. In the second stage, adapting to the posterior information obtained, narrow beams are then deployed to probe a small set of most likely angular directions, based on which the channel estimation is performed. Numerical results validate the effectiveness of TSACE proposed and confirm its performance gain over a few CS baselines subject to the same total average number of measurements under multi-path environments.


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    Title :

    A Two-Stage Adaptive Channel Estimation Scheme for Millimeter-Wave Massive MIMO Communication


    Contributors:
    Cheng, Pengyuan (author) / Li, Min (author) / Zhang, Jiayu (author)


    Publication date :

    2022-06-01


    Size :

    615672 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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