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User Grouping and Scheduling for Joint Spatial Division and Multiplexing in FDD Massive MIMO System
National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
- 1 National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
- 2 National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
- 3 National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
- 4 National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
- 5 National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
International Journal of Communications, Network and System Sciences·Volume 10 (2017)·Pages 176–185·Published 14 August 2017·DOI10.4236/ijcns.2017.108B019
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Abstract
Massive multiple-input multiple-output (MIMO) is a key technology for the 5th Generation wireless communication systems. Joint spatial division and multiplexing (JSDM) method can reduce the cost of downlink training and feedback for CSIT of frequency-division duplexing (FDD) system. In this paper, we studied user grouping and user scheduling problems based on JSDM, and proposed an improved greedy user scheduling algorithm with lower complexity. Numerical results show that the user grouping and scheduling based on the proposed improved algorithm have much lower computational complexity while resulting in only a slight loss in system performance.
KeywordsMassive MIMOFDDJSDMUser Scheduling
- Larsson, E.G., Edfors, O., Tufvesson, F. and Marzetta, T.L. (2014) Massive MIMO for Next Generation Wireless Systems. IEEE Communications Magazine, 52, 186- 195. https://doi.org/10.1109/MCOM.2014.6736761
- Nam, Y.H., et al. (2013) Full-Dimension MIMO (FD-MIMO) for Next Generation Cellular Technology. IEEE Communications Magazine, 51, 172-179. https://doi.org/10.1109/MCOM.2013.6525612
- Rao, X. and Lau, V.K.N. (2014) Distributed Compressive CSIT Esti-mation and Feedback for FDD Multi-User Massive MIMO Systems. IEEE Transactions on Signal Processing, 62, 3261-3271. https://doi.org/10.1109/TSP.2014.2324991
- Choi, J., Love, D.J. and Bidigare, P. (2014) Downlink Training Tech-niques for FDD Massive MIMO Systems: Open-Loop and Closed-Loop Training with Memory. IEEE Journal of Selected Topics in Signal Processing, 8, 802-814. https://doi.org/10.1109/JSTSP.2014.2313020
- Nam, J., Adhikary, A., Ahn, J.Y. and Caire, G. (2014) Joint Spatial Di-vision and Multiplexing: Opportunistic Beamforming, User Grouping and Simplified Downlink Scheduling. IEEE Journal of Selected Topics in Signal Processing, 8, 876-890. https://doi.org/10.1109/JSTSP.2014.2313808
- Xu, Y., Yue, G., Prasad, N., Rangarajan, S. and Mao, S. (2014) User Grouping and Scheduling for Large Scale MIMO Systems with Two-Stage Precoding. 2014 IEEE International Conference on Communications (ICC), Sydney, NSW, 10-14 June 2014, 5197-5202. https://doi.org/10.1109/ICC.2014.6884146
- Adhikary, A., Nam, J., Ahn, J.Y. and Caire, G. (2013) Joint Spatial Divi-sion and Multiplexing—The Large-Scale Array Regime. IEEE Transactions on Information Theory, 59, 6441-6463. https://doi.org/10.1109/TIT.2013.2269476
- Xu, Y., Yue, G. and Mao, S. (2014) User Grouping for Massive MIMO in FDD Systems: New Design Methods and Analysis. IEEE Access, 2, 947-959. https://doi.org/10.1109/ACCESS.2014.2353297
- Lloyd, S. (1982) Least Squares Quantization in PCM. IEEE Transac-tions on Information Theory, 28, 129-137. https://doi.org/10.1109/TIT.1982.1056489