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Extending the user capacity of MU-MIMO systems with low detection complexity and receive diversity

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Abstract

Multiple-input multiple-output (MIMO) based technologies are considered as an integral part of the upcoming 5G communications to fulfil the ever-increasing demands of wireless applications with high spectral efficiency requirements. However, in uplink multiuser MIMO (MU-MIMO) channels, the number of allowed users is limited by the number of receive antennas associated with radio frequency (RF) chains at the base-station and the complexity burden of multiuser detection (MUD). In this paper, a novel group layer MU-MIMO scheme with low complexity MUD is proposed to increase the number of served users well beyond the available RF chains. By taking the advantage of power control and inherent path loss in cellular systems, the allowed users are divided into groups based on their received power. Efficient group power allocation and group layer MUD (GL-MUD) are utilized to provide a valuable tradeoff between complexity and achieved performance. Furthermore, when more receive antennas than RF chains is implemented, a generalized norm based antenna selection algorithm is proposed to enhance the error performance. Symbol error probability expressions are derived and the effectiveness of proposed scheme is demonstrated through numerical simulations compared with the conventional MU-MIMO and non-orthogonal multiple-access (NOMA) systems over Rayleigh fading channels. The results show a substantial increase in user capacity up to two-fold for the available number of RF chains. In addition, significant signal-to-noise ratio gain is achieved using GL-MUD compared with different MUD techniques.

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References

  1. Hoymann, C., Astely, D., Stattin, M., Wikstrom, G., Cheng, J., Hoglund, A., et al. (2016). LTE release 14 outlook. IEEE Communications Magazine, 54(6), 44–49.

    Article  Google Scholar 

  2. Zhao, N., Yu, F. R., & Leung, V. C. M. (2015). Opportunistic communications in interference alignment networks with wireless power transfer. IEEE Wireless Communication, 22(1), 88–95.

    Article  Google Scholar 

  3. Paulraj, A., Gore, D., Nabar, R., & Bolcskei, H. (2004). An overview of MIMO communications—A key to gigabit wireless. Proceedings of the IEEE, 92(2), 198–218.

    Article  Google Scholar 

  4. Miao, G. (2013). Energy-efficient uplink multi-user MIMO. IEEE Transactions on Wireless Communications, 12(5), 2302–2313.

    Article  Google Scholar 

  5. Jungnickel, V., Manolakis, K., Zirwas, W., Panzner, B., et al. (2014). The role of small cells, coordinated multipoint, and massive MIMO in 5G. IEEE Communications Magazine, 52(2), 44–51.

    Article  Google Scholar 

  6. Xie, H., Wang, B., Gao, F., & Jin, S. (2016). A full-space specrum-sharing strategy for massive MIMO cognitive radio systems. IEEE Journal on Selected Areas in Communications, 34(10), 2537–2549.

    Article  Google Scholar 

  7. Bjornson, E., Larsson, E., & Debbah, M. (2016). Massive MIMO for maximal spectral efficiency: how many users and pilots should be allocated. IEEE Transactions on Wireless Communications, 15(2), 1293–1308.

    Article  Google Scholar 

  8. Parkvall, S., Furuskar, A., et al. (2011). Evolution of LTE toward IMT-advanced. IEEE Communications Magazine, 49(2), 84–91.

    Article  Google Scholar 

  9. Tse, D., Viswanath, P., & Zheng, L. (2004). Diversity-multiplexing tradeoff in multiple-access channels. IEEE Transactions on Information Theory, 50(9), 1859–1874.

    Article  MathSciNet  MATH  Google Scholar 

  10. Soysal, A., & Ulukus, S. (2010). Joint channel estimation and resource allocation for MIMO systems—PartII: Multi-user and numerical analysis. IEEE Transactions on Wireless Communications, 9(2), 632–640.

    Article  Google Scholar 

  11. Ding, Z., Adachi, F., & Poor, H. (2016). The application of MIMO to non-orthogonal multiple access. IEEE Transactions on Wireless Communications, 15(1), 537–552.

    Article  Google Scholar 

  12. Zafar, A., Shaqfeh, M., Alouini, M., & Alnuweiri, H. (2013). On multiple users scheduling using superposition coding over Rayleigh fading channel. IEEE Communications Letters, 17(4), 733–736.

    Article  Google Scholar 

  13. Sugiura, S., Chen, S., & Hanzo, L. (2012). MIMO-aided near-capacity turbo transceivers: taxonomy and performance versus complexity. IEEE Communcations Surveys and Tutorials, 14(2), 421–442.

    Article  Google Scholar 

  14. Zhu, X., & Murch, R. (2002). Performance analysis of maximum likelihood detection in a MIMO antenna system. IEEE Transactions on Communications, 50(2), 187–191.

    Article  Google Scholar 

  15. Zanella, A., Chiani, M., & Win, M. (2005). MMSE reception and successive interferance cancellation for MIMO systems with high spectral efficiency. IEEE Transactions on Wireless Communications, 4(3), 1244–1251.

    Article  Google Scholar 

  16. Sah, A. A. K., & Chaturvedi, A. (2016). An MMP based approach for detection in large MIMO systems using sphere decoding. IEEE Wireless Communcations Letters, 6(1), 1–4. doi: 10.1109/LWC.2016.2646368.

    Google Scholar 

  17. Zarikoff, B., Cavers, J., & Bavarian, S. (2007). An iterative groupwise multiuser detector for overloaded MIMO applications. IEEE Transactions on Wireless Communications, 6(2), 443–447.

    Article  Google Scholar 

  18. Al-Hussaibi, W., & Ali, F. (2013). Fast receive antenna selection for spatial multiplexing MIMO over correlated Rayleigh fading channels. Wireless Personal Communcations, 70(4), 1243–1259.

    Article  Google Scholar 

  19. Xu, Z., Sfar, S., & Blum, R. (2009). Analysis of MIMO systems with receive antenna selection in spatially correlated Rayleigh fading channels. IEEE Transactions on Vehicular Technology, 58(1), 251–262.

    Article  Google Scholar 

  20. Amadori, P., & Masouros, C. (2016). Interference-driven antenna selection for massive multiuser MIMO. IEEE Transactions on Vehicular Technology, 65(8), 5944–5958.

    Article  Google Scholar 

  21. Mehta, N., Kashyap, S., & Molisch, A. (2012). Antenna selection in LTE: From motivation to specification. IEEE Communications Magazine, 50(10), 144–150.

    Article  Google Scholar 

  22. Haci, H., Zhu, H., & Wang, J. (2017). Performance of non-orthogonal multiple access (NOMA) with a novel asynchronous interference cancellation technique. IEEE Transactions on Communications, 99, 1. doi:10.1109/TCOMM.2016.2640307.

    Google Scholar 

  23. Sari, H., Vanhaverbeke, F., & Moeneclaey, M. (2000). Extending the capacity of multiple access channels. IEEE Communications Magazine, 38, 74–82.

    Article  Google Scholar 

  24. Bopping, S. & Shea, J.M. (2006), “Superposition coding in the downlink of CDMA celluar systems,” In Proceedings IEEE WCNC’06, 4, 1978–1983.

  25. Yang, L. L. (2006). MIMO-assisted space-code-division multiple-access: linear detectors and performance over multipath fading channels. IEEE Journal on Selected Areas in Communications, 24(1), 121–131.

    Article  MathSciNet  Google Scholar 

  26. Ali, F., & Shakya, I. (2010). Collaborative spreading for the downlink of overloaded CDMA. Wireless Communcations and Mobile Computing, 10(3), 383–393.

    Google Scholar 

  27. Peters, S., & Heath, R., Jr. (2012). User partitioning for less overhead in MIMO interference channels. IEEE Transactions Wireless Communication, 11(2), 592–603.

    Article  Google Scholar 

  28. Tse, D., & Viswanath, P. (2005). Fundamentals of wireless communication. Cambridge: Cambridge Univ Press.

    Book  MATH  Google Scholar 

  29. Proakis, J. G. (2001). Digital communications (4th ed.). New York: McGraw-Hill.

    MATH  Google Scholar 

  30. Keshavarz, H., Xie, L.-L., & Mazumdar, R. (2009). User capacity scaling laws for fading multiple-access channels. IEEE Transactions on Wireless Communications, 8(9), 4498–4507.

    Article  Google Scholar 

  31. Al-Hussaibi, W., & Ali, F. (2012). Generation of correlated Rayleigh fading channels for accurate simulation of promising wireless communication systems. Simulation Modelling Practice and Theory, 25(4), 56–72.

    Article  Google Scholar 

  32. Al-Imari M., Xiao P., Imran M. A. & Tafazolli R, (2014) “Uplink non-orthogonal multiple access for 5G wireless networks,” In Proceedings 11th IEEE ISWCS, pp. 781–785.

  33. Tillo, T., Baccaglini, E., & Olmo, G. (2011). Unequal Protection of video data according to slice relevance. IEEE Transactions on Image Processing, 20(6), 1572–1582.

    Article  MathSciNet  MATH  Google Scholar 

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Authors and Affiliations

  1. Department of Electrical Techniques, BTI, Southern Technical University, Basrah, 42001, Iraq

    Walid A. Al-Hussaibi

  2. Communications Research Group, School of Engineering and Informatics, University of Sussex, Brighton, BN19QT, UK

    Falah H. Ali

Authors
  1. Walid A. Al-Hussaibi
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  2. Falah H. Ali
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Correspondence to Walid A. Al-Hussaibi.

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Al-Hussaibi, W.A., Ali, F.H. Extending the user capacity of MU-MIMO systems with low detection complexity and receive diversity. Wireless Netw 24, 2237–2249 (2018). https://doi.org/10.1007/s11276-017-1467-4

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  • DOI: https://doi.org/10.1007/s11276-017-1467-4

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