Massive multiple-input multiple-output (MIMO) is a technology that uses many antennas at base station (BS), and can realize advanced beamforming and spatial multiplexing. However, since Massive MIMO has many antennas, there exist problems such as the increase of overhead including pilot signals used for channel estimation and feedback of channel state information (CSI). To reduce the overhead, there is a technique of transmitting pilot signals only from some antennas and obtaining channels of the remaining antennas by the minimum mean square error (MMSE) interpolation based on spatial correlation. In addition, to perform the MMSE interpolation with low computational complexity, there is a method of interpolating channels by dividing the uniform rectangular antenna array (URA) into the vertical and horizontal linear directions. However, there is a problem that channel interpolation accuracy becomes low with dividing into the linear arrays. In this paper, we propose a method of channel interpolation with dividing the entire URA into a set of smaller URAs where interpolation is performed in each URA. Through computer simulation we show that the proposed method reduces the computational complexity compared with that without dividing, and improves the channel interpolation accuracy compared with that with dividing into linear arrays.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Low Complexity and High Accuracy Channel Interpolation with Dividing URA into Small URAs for 3D Massive MIMO


    Contributors:


    Publication date :

    2019-09-01


    Size :

    544856 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Adaptive Channel Interpolation in High-Speed Massive MIMO

    Osinsky, Alexander / Bychkov, Roman / Ivanov, Andrey et al. | IEEE | 2021




    Robust Low Complexity Beamforming for Cell-Free Massive MIMO

    Li, Na / Jin, Jing / Xia, Liang et al. | IEEE | 2020


    Ordered Iterative Methods for Low-Complexity Massive MIMO Detection

    Gong, Beilei / Zhou, Ningxin / Wang, Zheng | IEEE | 2023