inis 22(4): e3

Research Article

Phase Impairment Estimation for mmWave MIMO Systems with Low Resolutions ADC and Imperfect CSI

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  • @ARTICLE{10.4108/eetinis.v9i4.2467,
        author={Nguyen Dinh Ngoc and Kien Truong},
        title={Phase Impairment Estimation for mmWave MIMO Systems with Low Resolutions ADC and Imperfect CSI},
        journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems},
        volume={9},
        number={4},
        publisher={EAI},
        journal_a={INIS},
        year={2022},
        month={10},
        keywords={Hybrid analog and digital beamforming,, Non-ideal hardware, Phase noise estimation, Millimeter wave MIMO, Imperfect CSI, Quantization noise},
        doi={10.4108/eetinis.v9i4.2467}
    }
    
  • Nguyen Dinh Ngoc
    Kien Truong
    Year: 2022
    Phase Impairment Estimation for mmWave MIMO Systems with Low Resolutions ADC and Imperfect CSI
    INIS
    EAI
    DOI: 10.4108/eetinis.v9i4.2467
Nguyen Dinh Ngoc1,*, Kien Truong2
  • 1: Telecommunications University, Khanh Hoa, Vietnam
  • 2: Fulbright University Vietnam
*Contact email: nguyendinhngoc@tcu.edu.vn

Abstract

Multiple-Input Multiple-Output systems operating at millimeter wave band (mmWave MIMO) are a promising technology next generations of mobile networks. In practice, the non-ideal hardware is a challenge for commercially viable mmWave MIMO transceivers and come from non-linearities of the amplifier, phase noise, quantization errors, mutual coupling between antenna ports, and In-phase/Quadrature (I/Q) imbalance. As a result, the received signals are affected by non-ideal transceiver hardware components, thus reduce the performance of such systems, especially phase impairment caused by phase noise and carrier frequency offset (CFO). In this paper, we consider a mmWave MIMO system model that takes into account many practical hardware impairments and imperfect channel state information (CSI). Our main contributions are a problem formulation of phase impairments with imperfect CSI and a low-complexity estimation method to solve the problem. Numerical results are provided to evaluate the performance of the proposed algorithm.