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Optimal Transmitter Design and Pilot Spacing in MIMO Non-Stationary Aging Channels (2405.07895v2)

Published 13 May 2024 in eess.SP, cs.IT, and math.IT

Abstract: This work considers an uplink wireless communication system where multiple users with multiple antennas transmit data frames over dynamic channels. Previous studies have shown that multiple transmit and receive antennas can substantially enhance the sum-capacity of all users when the channel is known at the transmitter and in the case of uncorrelated transmit and receive antennas. However, spatial correlations stemming from close proximity of transmit antennas and channel variation between pilot and data time slots, known as channel aging, can substantially degrade the transmission rate if they are not properly into account. In this work, we provide an analytical framework to concurrently exploit both of these features. Specifically, we first propose a beamforming framework to capture spatial correlations. Then, based on random matrix theory tools, we introduce a deterministic expression that approximates the average sum-capacity of all users. Subsequently, we obtain the optimal values of pilot spacing and beamforming vectors upon maximizing this expression. Simulation results show the impacts of path loss, velocity of mobile users and Rician factor on the resulting sum-capacity and underscore the efficacy of our methodology compared to prior works.

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References (23)
  1. W. Rhee, W. Yu, and J. M. Cioffi, “The optimality of beamforming in uplink multiuser wireless systems,” IEEE Transactions on Wireless Communications, vol. 3, no. 1, pp. 86–96, 2004.
  2. F. Rusek, D. Persson, B. K. Lau, E. G. Larsson, T. L. Marzetta, O. Edfors, and F. Tufvesson, “Scaling up mimo: Opportunities and challenges with very large arrays,” IEEE signal processing magazine, vol. 30, no. 1, pp. 40–60, 2012.
  3. S. A. Jafar, S. Vishwanath, and A. Goldsmith, “Channel capacity and beamforming for multiple transmit and receive antennas with covariance feedback,” in ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No. 01CH37240), vol. 7.   IEEE, 2001, pp. 2266–2270.
  4. S. A. Jafar and A. Goldsmith, “Transmitter optimization and optimality of beamforming for multiple antenna systems,” IEEE Transactions on Wireless Communications, vol. 3, no. 4, pp. 1165–1175, 2004.
  5. L. Lu, G. Y. Li, A. L. Swindlehurst, A. Ashikhmin, and R. Zhang, “An overview of massive mimo: Benefits and challenges,” IEEE journal of selected topics in signal processing, vol. 8, no. 5, pp. 742–758, 2014.
  6. A. Soysal and S. Ulukus, “Optimality of beamforming in fading mimo multiple access channels,” IEEE transactions on communications, vol. 57, no. 4, pp. 1171–1183, 2009.
  7. “How much training is needed in multiple-antenna wireless links?” IEEE Transactions on Information Theory, vol. 49, no. 4, pp. 951–963, 2003.
  8. G. Fodor, N. Rajatheva, W. Zirwas, L. Thiele, M. Kurras, K. Guo, A. Tolli, J. H. Sorensen, and E. De Carvalho, “An overview of massive MIMO technology components in METIS,” IEEE Communications Magazine, vol. 55, no. 6, pp. 155–161, 2017.
  9. K. T. Truong and R. W. Heath, “Effects of channel aging in massive MIMO systems,” Journal of Communications and Networks, vol. 15, no. 4, pp. 338–351, 2013.
  10. S. Fodor, G. Fodor, D. Gürgünoğlu, and M. Telek, “Optimizing pilot spacing in MU-MIMO systems operating over aging channels,” IEEE Transactions on Communications, vol. 71, pp. 3708–3720, 2023.
  11. Z. Lian, L. Jiang, C. He, and D. He, “A non-stationary 3-D wideband GBSM for HAP-MIMO communication systems,” IEEE Transactions on Vehicular Technology, vol. 68, no. 2, pp. 1128–1139, 2018.
  12. G. Fodor, S. Fodor, and M. Telek, “Performance analysis of a linear MMSE receiver in time-variant rayleigh fading channels,” IEEE Transactions on Communications, vol. 69, no. 6, pp. 4098–4112, 2021.
  13. G. Fodor, S.Fodor, and M.Telek, “MU-MIMO receiver design and performance analysis in time-varying Rayleigh fading,” IEEE Transactions on Communications, vol. 70, no. 2, pp. 1214–1228, 2022.
  14. H. Abeida, “Data-aided SNR estimation in time-variant Rayleigh fading channels,” IEEE Transactions on Signal Processing, vol. 58, no. 11, pp. 5496–5507, Nov. 2010.
  15. H. Hijazi and L. Ros, “Joint data QR-detection and Kalman estimation for OFDM time-varying Rayleigh channel complex gains,” IEEE Transactions on Communications, vol. 58, no. 1, pp. 170–177, Jan. 2010.
  16. C. Kong, C. Zhong, A. K. Papazafeiropoulos, M. Matthaiou, and Z. Zhang, “Sum-rate and power scaling of massive MIMO systems with channel aging,” IEEE Transactions on Communications, vol. 63, no. 12, pp. 4879–4893, 2015.
  17. J. Yuan, H. Q. Ngo, and M. Matthaiou, “Machine learning-based channel prediction in massive MIMO with channel aging,” IEEE Transactions on Wireless Communications, vol. 19, no. 5, pp. 2960–2973, 2020.
  18. H. Kim, S. Kim, H. Lee, C. Jang, Y. Choi, and J. Choi, “Massive MIMO channel prediction: Kalman filtering vs. machine learning,” IEEE Transactions on Communications, pp. 1–1, 2020, early access.
  19. S. Daei, G. Fodor, M. Skoglund, and M. Telek, “Towards optimal pilot spacing and power control in multi-antenna systems operating over non-stationary rician aging channels,” arXiv preprint arXiv:2401.13368, 2024.
  20. J. Hoydis, S. T. Brink, and M. Debbah, “Massive MIMO in the UL/DL of cellular networks: How many antennas do we need ?” IEEE Journal on Selected Areas in Communications, vol. 31, no. 2, pp. 160–171, Feb. 2013.
  21. R. Couillet, M. Debbah, and J. W. Silverstein, “A deterministic equivalent for the analysis of correlated MIMO multiple access channels,” IEEE Transactions on Information Theory, vol. 57, no. 6, pp. 3493–3514, 2011.
  22. W. Hachem, P. Loubaton, and J. Najim, “Deterministic equivalents for certain functionals of large random matrices,” 2007.
  23. X. Gao, M. Sitharam, and A. E. Roitberg, “Bounds on the jensen gap, and implications for mean-concentrated distributions,” arXiv preprint arXiv:1712.05267, 2017.

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