期刊论文详细信息
ETRI Journal
Beamforming for Downlink Multiuser MIMO Time-Varying Channels Based on Generalized Eigenvector Perturbation
关键词: time-varying channels;    perturbation theory;    generalized eigendecomposition;    beamforming;    downlink;    MU-MIMO;   
Others  :  1186183
DOI  :  10.4218/etrij.12.1812.0090
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【 摘 要 】

A beam design method based on signal-to-leakage-plus-noise ratio (SLNR) has been recently proposed as an effective scheme for multiuser multiple-input multiple-output downlink channels. It is shown that its solution, which maximizes the SLNR at a transmitter, can be simply obtained by the generalized eigenvectors corresponding to the dominant generalized eigenvalues of a pair of covariance matrices of a desired signal and interference leakage plus noise. Under time-varying channels, however, generalized eigendecomposition is required at each time step to design the optimal beam, and its level of complexity is too high to implement in practical systems. To overcome this problem, a predictive beam design method updating the beams according to channel variation is proposed. To this end, the perturbed generalized eigenvectors, which can be obtained by a perturbation theory without any iteration, are used. The performance of the method in terms of SLNR is analyzed and verified using numerical results.

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【 参考文献 】
  • [1]M.H.M. Costa, "Writing on Dirty Paper," IEEE Trans. Inf. Theory, vol. 29, no. 3, May 1983, pp. 439-441.
  • [2]N. Jindal and A. Goldsmith, "Dirty Paper Coding vs. TDMA for MIMO Broadcast Channels," IEEE Trans. Inf. Theory, vol. 51, no. 5, May 2005, pp. 1783-1794.
  • [3]U. Erez and S.T. Brink, "A Close-to-Capacity Dirty Paper Coding Scheme," IEEE Trans. Inf. Theory, vol. 51, no. 10, Oct. 2005, pp. 1783-1794.
  • [4]P. Viswanath and D. Tse, "Sum Capacity of Gaussian Vector Broadcast Channels," IEEE Trans. Inf. Theory, vol. 49, no. 8, Aug. 2003, pp. 1912-1921.
  • [5]G. Caire and S. Shamai, "On the Achievable Throughput of a Multi-antenna Gaussian Broadcast Channel," IEEE Trans. Inf. Theory, vol. 49, no. 7, July 2003, pp. 1691-1706.
  • [6]Q.H. Spencer, A.L. Swindlehurst, and M. Haardt, "Zero-Forcing Methods for Downlink Spatial Multiplexing in Multi-user MIMO Channels," IEEE Trans. Signal Process., vol. 52, no. 2, Feb. 2004, pp. 461-471.
  • [7]C.B. Peel, B.M. Hochwald, and A.L. Swindlehurst, "A Vector Perturbation Technique for Near-Capacity Multi-antenna Multiuser Communication – Part I: Channel Inversion and Regularization," IEEE Trans. Commun., vol. 53, no. 1, Jan. 2005, pp. 195-202.
  • [8]M. Sadek, A. Tarighat, and A.H. Sayed, "A Leakage-Based Precoding Scheme for Downlink Multi-user MIMO Channels," IEEE Trans. Wireless Commun., vol. 6, no. 5, May 2007, pp. 1711-1721.
  • [9]M. Dong, L. Tong, and B.M. Sadler, "Optimal Insertion of Pilot Symbols for Transmissions over Time-Varying Flat Fading Channels," IEEE Trans. Signal Process., vol. 52, no. 5, May 2004, pp. 1403-1418.
  • [10]M. Medard, "The Effects upon Channel Capacity in Wireless Communications of Perfect and Imperfect Knowledge of the Channel," IEEE Trans. Inf. Theory, vol. 46, no. 5, May 2000, pp. 933-946.
  • [11]C. Komninakis et al., "Multi-input Multi-output Fading Channel Tracking and Equalization Using Kalman Estimation," IEEE Trans. Signal Process., vol. 50, no. 5, May 2002, pp. 1065-1076.
  • [12]H. Yu et al., "Beam Tracking for Interference Alignment in Slowly-Fading MIMO Interference Channels: A Perturbations Approach Under a Linear Framework," IEEE Trans. Signal Process., vol. 60, no. 4, Apr. 2012, pp. 1910-1926.
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