Hybrid precoding/combining (HPC) architecture is a promising candidate for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. It is capable of reducing the hardware cost/complexity and power consumption compared to the full-digital precoding/combining (FDPC) while keeping the similar spectral efficiency. Most of the prior works on HPC consider the availability of full channel state information (CSI) to design both radio-frequency (RF) and baseband (BB) stages. In this work, an angular-based HPC (AB-HPC) design requiring low CSI overhead is proposed for mmWave massive MIMO systems equipped with low-resolution digital-to-analog converters (DAC) and analog-to-digital converters (ADC). Based on the 3D geometry-based mmWave channel model, the transmit and receive RF beamformers are first developed based on the slow time-varying angle-of-departure (AoD) and angle-of-arrival (AoA) parameters, respectively. Then, the transmit BB precoder and receive BB combiner are designed by employing the reduced-size effective CSI seen from the BB-stages. Considering the effect of low-resolution DACs/ADCs, the receive BB combiner is obtained by the minimum mean square error (MMSE) criterion. The numerical results reveal that the proposed AB-HPC technique can closely approach the achievable rate performance of FDPC while remarkably reducing the number of power-hungry RF chains and CSI overhead size (e.g., around 94.1% – 98.5%). Moreover, the quantization error occurred due to the low-resolution DACs/ADCs causes a performance floor. For a given signal-to-noise ratio (SNR), we also ask the required number of bits for the low-resolution DACs/ADCs for converging to the same achievable rate performance in full-precision DACs/ADCs.


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    Title :

    Hybrid Millimeter-Wave Massive MIMO Systems with Low CSI Overhead and Few-Bit DACs/ADCs


    Contributors:
    Koc, Asil (author) / Le-Ngoc, Tho (author)


    Publication date :

    2020-11-01


    Size :

    1682570 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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