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SCIENCE CHINA Information Sciences, Volume 61, Issue 8: 082302(2018) https://doi.org/10.1007/s11432-017-9353-8

User scheduling for downlink FD-MIMO systems under Rician fading exploiting statistical CSI

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  • ReceivedNov 14, 2017
  • AcceptedJan 24, 2018
  • PublishedApr 27, 2018

Abstract

In this paper, we consider the user scheduling algorithm for downlink full-dimension multiple-input multiple-output (FD-MIMO) system under Rician fading channels. We assume that two-dimensional (2D) large-scale antenna array is deployed at base station (BS). An approximation of user's signal-to-interference-plus-noise ratio (SINR) and a lower bound of user's average signal-to-leakage-plus-noise ratio (SLNR) are derived. Based on these, two user scheduling algorithms exploiting only statistical channel state information (CSI) are proposed. The proposed algorithms take both the achievable sum rate and fairness into account. Simulation results reveal that the proposed user scheduling algorithms can make good trade-off between the achievable rate and fairness.


Acknowledgment

This work was supported by National Natural Science Foundation of China (Grant Nos. 61571112, 61531011, 61625106, 61320106003, 61521061), Foundation for the Author of National Excellent Doctoral Dissertation of PR China (FANEDD) (Grant No. 201446), and Fundamental Research Funds for the Central Universities (Grant No. 2242015R30006).


Supplement

Appendix

Proof of Theorem 1

Appendix A.


References

[1] Rusek F, Persson D, Lau B K, et al. Scaling up MIMO: opportunities and challenges with very large arrays. IEEE Signal Process Mag, 2013, 30: 40--60. Google Scholar

[2] You X H, Pan Z W, Gao X Q, et al. The 5G mobile communication: the development trends and its emerging key techniques (in Chinese). Sci Sin Inform, 2014, 44: 551--563. Google Scholar

[3] Wang D M, Zhang Y, Wei H. An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications. Sci China Inf Sci, 2016, 59: 081301 CrossRef Google Scholar

[4] Wang C-X, Wu S B, Bai L, et al. Recent advances and future challenges for massive MIMO channel measurements and models. Sci China Inf Sci, 2016, 59: 021301. Google Scholar

[5] Marzetta T L. Noncooperative cellular wireless with unlimited numbers of base station antennas. IEEE Trans Wireless Commun, 2010, 9: 3590-3600 CrossRef Google Scholar

[6] Hien Quoc Ngo , Larsson E G, Marzetta T L. Energy and spectral efficiency of very large multiuser MIMO systems. IEEE Trans Commun, 2013, 61: 1436-1449 CrossRef Google Scholar

[7] Nam Y H, Ng B L, Sayana K, et al. Full-dimension MIMO (FD-MIMO) for next generation cellular technology. IEEE Commun Mag, 2013, 51: 172--186. Google Scholar

[8] Kim Y, Ji H, Lee J, et al. Full dimension MIMO (FD-MIMO): the next evolution of MIMO in LTE systems. IEEE Wireless Commun, 2014, 21: 26--33. Google Scholar

[9] Adhikary A, Junyoung Nam A, Jae-Young Ahn A. Joint spatial division and multiplexing-the large-scale array regime. IEEE Trans Inform Theor, 2013, 59: 6441-6463 CrossRef Google Scholar

[10] Xu W. Capacity improvement analysis of 3D-beamforming in small cell systems. Sci China Inf Sci, 2018, 61: 022305 CrossRef Google Scholar

[11] Mao J L, Gao J C, Liu Y A. Robust multiuser MIMO scheduling algorithms with imperfect CSI. Sci China Inf Sci, 2012, 55: 815-826 CrossRef Google Scholar

[12] Marzetta T L, Caire G, Debbah M, et al. Special issue on massive MIMO. J Commun Netw, 2013, 59: 333--337. Google Scholar

[13] Chan P W C, Lo E S, Wang R R, et al. The evolution path of 4G networks: FDD or TDD? IEEE Commun Mag, 2006, 44: 42--50. Google Scholar

[14] Nam J, Adhikary A, Ahn J-Y, et al. Joint spatial division and multiplexing: opportunistic beamforming, user grouping and simplified downlink scheduling. IEEE J Sel Topics Signal Process, 2013, 8: 876--890. Google Scholar

[15] Li X, Jin S, Gao X. Three-dimensional beamforming for large-scale FD-MIMO systems exploiting statistical channel state information. IEEE Trans Veh Technol, 2016, 65: 8992-9005 CrossRef Google Scholar

[16] Li X, Jin S, Suraweera H A. Statistical 3-D beamforming for large-scale MIMO downlink systems over Rician fading channels. IEEE Trans Commun, 2016, 64: 1529-1543 CrossRef Google Scholar

[17] Han Y, Zhang H, Jin S. Investigation of transmission schemes for millimeter-wave massive MU-MIMO systems. IEEE Syst J, 2017, 11: 72-83 CrossRef ADS Google Scholar

[18] Maddah-Ali M A, Tse D. Completely stale transmitter channel state information is still very useful. IEEE Trans Inform Theor, 2012, 58: 4418-4431 CrossRef Google Scholar

[19] Adhikary A, Dhillon H S, Caire G. Massive-MIMO meets HetNet: interference coordination through spatial blanking. IEEE J Sel Areas Commun, 2015, 33: 1171-1186 CrossRef Google Scholar

[20] Sadek M, Tarighat A, Sayed A. A leakage-based precoding scheme for downlink multi-user MIMO channels. IEEE Trans Wireless Commun, 2007, 6: 1711-1721 CrossRef Google Scholar

[21] Xia X, Wu G, Liu J. Leakage-based user scheduling in MU-MIMO broadcast channel. Sci China Ser F-Inf Sci, 2009, 52: 2259-2268 CrossRef Google Scholar

[22] Mullen K. A note on the ratio of two independent random variables. Amer Stat, 1967, 21: 30--31. Google Scholar

[23] Sediq A B, Gohary R H, Schoenen R. Optimal tradeoff between sum-rate efficiency and Jain's fairness index in resource allocation. IEEE Trans Wireless Commun, 2013, 12: 3496-3509 CrossRef Google Scholar

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