Skip to main content
Log in

Joint user grouping and resource allocation for uplink virtual MIMO systems

上行虚拟MIMO系统的联合用户配对和资源分配算法

  • Research Paper
  • Special Focus on 5G Wireless Communication Networks
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

Abstract

MIMO has become a core technology of 5G network to largely improve system throughput. Due to the cost and size of the user equipment (UE), the application of MIMO uplink is limited by the difficulty in practical implementation at the user side. Virtual MIMO has been widely investigated to solve this problem for wireless uplink systems. However, virtual MIMO transmission leads to performance degradation due to the multiuser interference. To obtain good trade-off between the system throughput and transmission performance, we investigate joint user grouping and resource allocation under the consideration of system throughput and average mean squared error (MSE) performance in SC-FDMA uplink systems. Based on linear MIMO detection, we first develop MSE-oriented user grouping criteria for evaluation of transmission performance, then establish dynamic user grouping and optimal resource allocation problems for hard and elastic average MSE constraints. The proposed joint resource allocation algorithm is evaluated in SC-FDMA uplink scenarios and the results show that it achieves maximum system throughput with average MSE guaranteed for the hard MSE constraint algorithms and the alterable trade-off between system throughput and average MSE for the elastic MSE constraint algorithms.

创新点

  1. 1

    提出与量化评价基于平均MSE的用户分组准则。为了降低计算复杂度,并利用矩阵的最小特征值及其估计值推导出了两种形式的次优用户分组标准

  2. 2

    根据用户配对准则和上行SC-FDMA的资源块分配准则,提出了联合用户配对和资源分配算法。以系统吞吐量和系统平均MSE为多目标函数,构建多目标优化模型

  3. 3

    在硬MSE约束的应用场景下,通过使用MSE约束来使得多目标函数单目标化;在弹性MSE约束的应用场景下,通过赋予吞吐量和MSE值不同的权值来使得多目标函数单目标化;将简化后的优化模式使用分支定界法来求解。

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Paulraj A J, Gore D A, Nabar R U, et al. An overview of MIMO communications-a key to gigabit wireless. Proc IEEE, 2004, 92: 198–218

    Article  Google Scholar 

  2. Nortel. UL virtual MIMO transmission for E-UTRA. In: 3GPP TSG RAN WG Meeting #42, R1-051162, 2005. 1–10

    Google Scholar 

  3. Sesia S, Toufik I, Baker M. LTE, the UMTS Long Term Evolution: From Theory to Practice. New York: John Wiley & Sons, 2009

    Book  Google Scholar 

  4. Motorola. Link simulation results for uplink virtual MIMO. In: 3GPP TSG RAN WG Meeting #54, R1-062074, 2006. 1–3

    Google Scholar 

  5. Wang C X, Hong X M, Ge X H, et al. Cooperative MIMO channel models: a survey. IEEE Commun Mag, 2010, 48: 80–87

    Article  Google Scholar 

  6. Zhao H T, Emiliano G P, Wei J B, et al. Capacity and resource allocation of cooperative MIMO in ad hoc networks. Phys Commun, 2011, 4: 98–110

    Article  Google Scholar 

  7. Zhao H Z, Ma S, Liu F W, et al. A suboptimal multiuser pairing algorithm with low complexity for virtual MIMO systems. IEEE Trans Veh Technol, 2014, 63: 3481–3486

    Article  Google Scholar 

  8. Goldsmith A, Jafar S A, Jindal N, et al. Capacity limits of MIMO channels. IEEE J Sel Area Commun, 2003, 21: 684–702

    Article  Google Scholar 

  9. Qualcomm Europe. UL system analysis with SDMA. In: 3GPP TSG RAN WG Meeting #45, R1-062052, 2006. 1–8

    Google Scholar 

  10. Fan J C, Li G Y, Yin Q Y, et al. Joint user pairing and resource allocation for LTE uplink transmission. IEEE Trans Wirel Commun, 2012, 11: 2838–2847

    Google Scholar 

  11. Fan B, Wang W B, Lin Y C, et al. Spatial multi-user pairing for uplink virtual-MIMO systems with linear receiver. In: Proceedings of 2009 IEEE Wireless Communications & Networking Conference, Budapest, 2009. 1807–1811

    Google Scholar 

  12. Chen X, Hu H L, Wang H F, et al. Double proportional fair user pairing algorithm for uplink virtual MIMO systems. IEEE Trans Wirel Commun, 2008, 7: 2425–2429

    Article  Google Scholar 

  13. Liang J, Liang Q L. Channel selection in virtual MIMO wireless sensor networks. IEEE Trans Veh Technol, 2009, 58: 2249–2257

    Article  Google Scholar 

  14. Nortel. UL virtual MIMO system level performance evaluation for E-UTRA. In: 3GPP TSG RAN1 WG1 Meeting #42, R1-051422, 2005. 1–6

    Google Scholar 

  15. Dhakal S, Joonbeom K. Statistical analysis of user-pairing algorithms in virtual MIMO systems. In: Proceedings of Wireless Telecommunications Symposium, Tampa, 2010. 1–5

    Google Scholar 

  16. Ruder M A, Ding D, Dang U L, et al. Joint user grouping and frequency allocation for multiuser SC-FDMA transmission. Phys Commun, 2013, 8: 91–103

    Article  Google Scholar 

  17. Li Y, Wang W B, Zhang X, et al. Combined proportional fair and maximum rate scheduling for virtual MIMO. In: Proceedings of 2008 IEEE 68th Vehicular Technology Conference, Calgary, 2008. 1–4

    Google Scholar 

  18. Wang X T, Wang W B, Zhao Z Y, et al. Fairness adjustable grouping multiuser scheduling for MIMO MAC with MMSE-SIC receiver. In: Proceedings of 2008 IEEE Globecom Workshops, New Orleans, 2008. 1–5

    Google Scholar 

  19. Karimi O B, Toutounchian M A, Liu J C, et al. Lightweight user grouping with flexible degrees of freedom in virtual MIMO. IEEE J Sel Area Commun, 2013, 31: 2004–2012

    Article  Google Scholar 

  20. Myung H G, Lim J S, Goodman D J. Single carrier FDMA for uplink wireless transmission. IEEE Trans Veh Technol, 2006, 1: 30–38

    Article  Google Scholar 

  21. Wong I C, Oteri O, Mc Coy W. Optimal resource allocation in uplink SC-FDMA systems. IEEE Trans Wirel Commun, 2009, 8: 2161–2165

    Article  Google Scholar 

  22. Prasad N, Zhang H H, Zhu H, et al. Multi-user MIMO scheduling in the fourth generation cellular uplink. IEEE Trans Wirel Commun, 2013, 12: 4272–4285

    Article  Google Scholar 

  23. Kuhn H. The Hungarian method for the assignment problem. Nav Res Log, 1955, 1: 83–97

    Article  MathSciNet  MATH  Google Scholar 

  24. Kuhn H. Variants of the Hungarian method for the assignment problem. Nav Res Log, 1956, 3: 253–258

    Article  Google Scholar 

  25. Rojo O. Further bounds for the smallest singular value and the spectral condition number. Comput Math Appl, 1999, 38: 215–228

    Article  MathSciNet  MATH  Google Scholar 

  26. Yu X Y, Gen M S. Introduction to Evolutionary Algorithms. London: Springer-Verlag, 2010. 193–259

    MATH  Google Scholar 

  27. Wei G H, Wang F. Linear Programming. Beijing: Higher Education Press, 1989. 205–225

    Google Scholar 

  28. International Telecommunication Union. Guidelines for evaluation of radio transmission technologies for IMT-2000. In: Recommendation ITU-RM, 1225, 1997. 1–60

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaofeng Lu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lu, X., Yang, K., Li, W. et al. Joint user grouping and resource allocation for uplink virtual MIMO systems. Sci. China Inf. Sci. 59, 1–14 (2016). https://doi.org/10.1007/s11432-015-5514-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11432-015-5514-4

Keywords

Keywords

关键词

Navigation