Robust hybrid beamforming design for millimeter-wave massive MIMO systems
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摘要
Hybrid analog-digital beamforming is recognized as a promising solution for a practical implementation of massive multiple-input multiple-output(MIMO) systems based on millimeter-wave(mmWave) technology. In view of the overwhelming hardware cost and excessive power consumption and the imperfection of the channel state information(CSI), a robust hybrid beamforming design is proposed for the mmWave massive MIMO systems, where the robustness is defined with respect to imperfect knowledge or error of the CSI at the transmitter due to limited feedback and/or imperfect channel estimation. Assuming the errors of the CSI are bounded, the optimal hybrid beamforming design with robustness is formulated to a mean squared error(MSE) minimization problem. An iterative semidefinite programming(SDP) based algorithm is proposed to obtain the beamforming matrices. Simulation results show that the proposed robust design can provide more than 4 dB performance gain compared to that of non-robust design.
Hybrid analog-digital beamforming is recognized as a promising solution for a practical implementation of massive multiple-input multiple-output(MIMO) systems based on millimeter-wave(mmWave) technology. In view of the overwhelming hardware cost and excessive power consumption and the imperfection of the channel state information(CSI), a robust hybrid beamforming design is proposed for the mmWave massive MIMO systems, where the robustness is defined with respect to imperfect knowledge or error of the CSI at the transmitter due to limited feedback and/or imperfect channel estimation. Assuming the errors of the CSI are bounded, the optimal hybrid beamforming design with robustness is formulated to a mean squared error(MSE) minimization problem. An iterative semidefinite programming(SDP) based algorithm is proposed to obtain the beamforming matrices. Simulation results show that the proposed robust design can provide more than 4 dB performance gain compared to that of non-robust design.
Hybrid analog-digital beamforming is recognized as a promising solution for a practical implementation of massive multiple-input multiple-output(MIMO) systems based on millimeter-wave(mmWave) technology. In view of the overwhelming hardware cost and excessive power consumption and the imperfection of the channel state information(CSI), a robust hybrid beamforming design is proposed for the mmWave massive MIMO systems, where the robustness is defined with respect to imperfect knowledge or error of the CSI at the transmitter due to limited feedback and/or imperfect channel estimation. Assuming the errors of the CSI are bounded, the optimal hybrid beamforming design with robustness is formulated to a mean squared error(MSE) minimization problem. An iterative semidefinite programming(SDP) based algorithm is proposed to obtain the beamforming matrices. Simulation results show that the proposed robust design can provide more than 4 dB performance gain compared to that of non-robust design.
引文
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11.Horn R A,Johnson C R.Matrix analysis.New York,NY,USA:Cambridge University Press,1985
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13.Eldar Y C,Merhav N.A competitive minimax approach to robust estimation of random parameters.IEEE Transactions on Signal Processing,2004,52(7):1931-1946
2.Buzzi S,Chih-Lin I,Klein T E,et al.A survey of energy-efficient techniques for 5G networks and challenges ahead.IEEE Journal on Selected Areas in Communications,2016,34(4):697-709
3.Rappaport T S,Sun S,Mayzus R,et al.Millimeter wave mobile communications for 5G cellular:it will work! IEEE Access,2013,1:335-349
4.Jungnickel V,Manolakis K,Zirwas W,et al.The role of small cells,coordinated multipoint,and massive MIMO in 5G.IEEE Communications Magazine,2014,52(5):44-51
5.Rangan S,Rappaport T S,Erkip E.Millimeter-wave cellular wireless networks:potentials and challenges.Proceedings of the IEEE,2014,102(3):366-385
6.Chen C E.An iterative hybrid transceiver design algorithm for millimeter wave MIMO systems.IEEE Wireless Communications Letters,2015,4(3):285-288
7.Yu X H,Shen J C,Zhang J,et al.Alternating minimization algorithms for hybrid precoding in millimeter wave MIMO systems.IEEE Journal of Selected Topics Signal Processing,2016,10(3):485-500
8.Awad M K,Mahinthan V,Mehrjoo M,et al.A dual-decomposition-based resource allocation for OFDMA networks with imperfect CSI.IEEE Transactions on Vehicular Technology,2010,59(5):2394-2403
9.Rappaport T S,Heath R W,Daniels R C,et al.Millimeter wave wireless communications.New York,NY,USA:Pearson Education,2014
10.Vucic N,Boche H,Shi S Y.Robust transceiver optimization in downlink multiuser MIMO systems.IEEE Transactions on Signal Processing,2009,57(9):3576-3587
11.Horn R A,Johnson C R.Matrix analysis.New York,NY,USA:Cambridge University Press,1985
12.Toh K C,Todd M J,Tütüncü R H.SDPT3—a Matlab software package for semidefinite programming,version 1.3.Optimization Methods and Software,1999,11(1/2/3/4):545-581
13.Eldar Y C,Merhav N.A competitive minimax approach to robust estimation of random parameters.IEEE Transactions on Signal Processing,2004,52(7):1931-1946