Advanced Search
Volume 45 Issue 7
Jul.  2023
Turn off MathJax
Article Contents
LIANG Yan, XIANG Caixia, LI Fei. A Hybrid Precoding Scheme for Millimeter Wave Massive MIMO System with Residual Hardware Impairments[J]. Journal of Electronics & Information Technology, 2023, 45(7): 2451-2458. doi: 10.11999/JEIT220724
Citation: LIANG Yan, XIANG Caixia, LI Fei. A Hybrid Precoding Scheme for Millimeter Wave Massive MIMO System with Residual Hardware Impairments[J]. Journal of Electronics & Information Technology, 2023, 45(7): 2451-2458. doi: 10.11999/JEIT220724

A Hybrid Precoding Scheme for Millimeter Wave Massive MIMO System with Residual Hardware Impairments

doi: 10.11999/JEIT220724
Funds:  The National Natural Science Foundation of China (61871238)
  • Received Date: 2022-06-22
  • Accepted Date: 2023-02-06
  • Rev Recd Date: 2022-10-14
  • Available Online: 2023-02-10
  • Publish Date: 2023-07-10
  • Based on the assumption of perfect transceiver hardware, the hybrid precoding of millimeter wave massive Multiple-Input Multiple-Output (MIMO) system has been extensively studied. However, the residual hardware impairments caused by non-ideal characteristics of transceivers are unavoidable in millimeter wave massive MIMO system, which lead to hybrid precoding performance degradation seriously. To address this problem, the hybrid precoding model which considers the impact of residual hardware impairments is built for millimeter wave massive MIMO system and a hybrid precoding scheme based on manifold optimization is proposed in this paper. Firstly, the optimization objective is designed with the modified mean square error. Then the closed-form expressions of the digital precoding and digital combining matrix are derived and the optimal solutions of the analog precoding matrix and the combining matrix are obtained by dealing with the constant modulus constraint on the Riemannian manifold. Finally, the joint hybrid precoding and combining design are achieved by iteratively and alternatively optimizing the hybrid precoding and the hybrid combining matrix. The simulation results show that the proposed scheme suppresses effectively the impact of residual hardware impairments on the millimeter-wave massive MIMO system, and improves significantly the system performance.
  • loading
  • [1]
    CHATAUT R and AKL R. Massive MIMO systems for 5G and beyond networks—overview, recent trends, challenges, and future research direction[J]. Sensors, 2020, 20(10): 2753. doi: 10.3390/s20102753
    [2]
    KEBEDE T, WONDIE Y, STEINBRUNN J, et al. Precoding and beamforming techniques in mmWave-massive MIMO: Performance assessment[J]. IEEE Access, 2022, 10: 16365–16387. doi: 10.1109/access.2022.3149301
    [3]
    DILLI R. Performance analysis of multi user massive MIMO hybrid beamforming systems at millimeter wave frequency bands[J]. Wireless Networks, 2021, 27(3): 1925–1939. doi: 10.1007/s11276-021-02546-w
    [4]
    HEGDE G, MASOUROS C, and PESAVENTO M. Interference exploitation-based hybrid precoding with robustness against phase errors[J]. IEEE Transactions on Wireless Communications, 2019, 18(7): 3683–3696. doi: 10.1109/twc.2019.2917064
    [5]
    LIN Tian, CONG Jiaqi, ZHU Yu, et al. Hybrid beamforming for millimeter wave systems using the MMSE criterion[J]. IEEE Transactions on Communications, 2019, 67(5): 3693–3708. doi: 10.1109/tcomm.2019.2893632
    [6]
    AYACH O E, RAJAGOPAL S, ABU-SURRA S, et al. Spatially sparse precoding in millimeter wave MIMO systems[J]. IEEE Transactions on Wireless Communications, 2014, 13(3): 1499–1513. doi: 10.1109/twc.2014.011714.130846
    [7]
    SOHRABI F and YU Wei. Hybrid analog and digital beamforming for mmWave OFDM large-scale antenna arrays[J]. IEEE Journal on Selected Areas in Communications, 2017, 35(7): 1432–1443. doi: 10.1109/jsac.2017.2698958
    [8]
    HAO Wanming, SUN Gangcan, ZENG Ming, et al. Robust design for intelligent reflecting surface-assisted MIMO-OFDMA terahertz IoT networks[J]. IEEE Internet of Things Journal, 2021, 8(16): 13052–13064. doi: 10.1109/jiot.2021.3064069
    [9]
    XING Zhe, WANG Rui, WU Jun, et al. Achievable rate analysis and phase shift optimization on intelligent reflecting surface with hardware impairments[J]. IEEE Transactions on Wireless Communications, 2021, 20(9): 5514–5530. doi: 10.1109/twc.2021.3068225
    [10]
    ZAREI S, GERSTACKER W H, AULIN J, et al. Multi-cell massive MIMO systems with hardware impairments: Uplink-downlink duality and downlink precoding[J]. IEEE Transactions on Wireless Communications, 2017, 16(8): 5115–5130. doi: 10.1109/twc.2017.2705709
    [11]
    PAPAZAFEIROPOULOS A K, PAPAGEORGIOU G K, KOLAWOLE O Y, et al. Towards the assessment of realistic hybrid precoding in millimeter wave MIMO systems with hardware impairments[J]. IET Communications, 2021, 15(12): 1606–1619. doi: 10.1049/cmu2.12173
    [12]
    PAPAZAFEIROPOULOS A, BJÖRNSON E, KOURTESSIS P, et al. Scalable cell-free massive MIMO systems: Impact of hardware impairments[J]. IEEE Transactions on Vehicular Technology, 2021, 70(10): 9701–9715. doi: 10.1109/tvt.2021.3109341
    [13]
    ORTEGA A J. OMP-based hybrid precoding and SVD-based hybrid combiner design with partial CSI for massive MU-MIMO mmWave system[C]. 2020 International Conference on Communications, Signal Processing, and their Applications (ICCSPA), Sharjah, United Arab Emirates, 2021: 1–5.
    [14]
    PALOMAR D P, CIOFFI J M, and LAGUNAS M A. Joint Tx-Rx beamforming design for multicarrier MIMO channels: A unified framework for convex optimization[J]. IEEE Transactions on Signal Processing, 2003, 51(9): 2381–2401. doi: 10.1109/tsp.2003.815393
    [15]
    JOHAM M, UTSCHICK W, and NOSSEK J A. Linear transmit processing in MIMO communications systems[J]. IEEE Transactions on signal Processing, 2005, 53(8): 2700–2712. doi: 10.1109/tsp.2005.850331
    [16]
    LEE J M. Introduction to Smooth Manifolds[M]. 2nd ed. New York: Springer, 2012.
    [17]
    YU Xianghao, SHEN J C, ZHANG Jun, et al. Alternating minimization algorithms for hybrid precoding in millimeter wave MIMO systems[J]. IEEE Journal of Selected Topics in Signal Processing, 2016, 10(3): 485–500. doi: 10.1109/jstsp.2016.2523903
    [18]
    HJORUNGNES A and PALOMAR D P. Patterned complex-valued matrix derivatives[C]. 2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop, Darmstadt, Germany, 2008: 293–297.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(6)  / Tables(2)

    Article Metrics

    Article views (430) PDF downloads(72) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return