Energy-Efficient Joint User Association and Power Allocation in Relay-Aided Massive MIMO Systems

Research paper


Energy efficiency is an important metric for downlink transmission in an amplify-and-forward relayaided massive multiple-input multiple-output system, but has not been well investigated. In this work, considering the characteristics of such a system and quality-of-service requirements of users, the energy-efficient joint user association and power allocation problem is studied. First, the closed-form expression of system energy efficiency under the proportional fairness criterion is derived. Then, the proportionally fair utility of system energy efficiency is maximized under constraints of minimum signal-to-noise ratio requirements of users and maximum transmit powers of the base station (BS) and relay stations. As it is difficult to solve this optimization problem directly due to its mixed-integer and non-convex features, the original problem is decomposed into a user association sub-problem and a power allocation sub-problem. For the former, optimum user association is determined by solving a Lagrangian dual problem with a sub-gradient algorithm; for the latter, optimum transmit powers of the BS and each relay station are determined by using Newton’s method. Finally, a sub-optimal solution of the original problem is obtained by a low-complexity iterative algorithm. Simulation results show that the proposed joint user association and power allocation algorithm can offload the traffic of the BS effectively, keep the BS and relay stations operate at low power levels, and improve the system energy efficiency significantly, compared with user association-only schemes.


massive MIMO relay energy efficiency user association power allocation 


  1. [1]
    M. Shafi, A. F. Molisch, P. J. Smith, et al. 5G: a tutorial overview of standards, trials, challenges, deployment and practice [J]. IEEE Journal on Selected Areas in Communications, 2017, 3(6): 1201–1221.CrossRefGoogle Scholar
  2. [2]
    S. Buzzi, I. Chih-Lin, T. E. Klein, et al. A survey of energy-efficient techniques for 5G networks and challenges ahead [J]. IEEE Journal on Selected Areas in Communications, 2016, 34(4): 697–709.CrossRefGoogle Scholar
  3. [3]
    T. L. Marzetta. Noncooperative cellular wireless with unlimited numbers of base station antennas [J]. IEEE Transactions on Wireless Communications, 2010, 9(11): 3590–3600.CrossRefGoogle Scholar
  4. [4]
    L. Lu, G. Y. Li, A. L. Swindlehurst, et al. An overview of massive MIMO: benefits and challenges [J]. IEEE Journal of Selected Topics in Signal Processing, 2014, 8(5): 742–758.CrossRefGoogle Scholar
  5. [5]
    M. Torab, D. Haccoun, J. F. Frigon. Relay selection in AF cooperative systems: an overview [J]. IEEE Vehicular Technology Magazine, 2012, 7(4): 104–113.CrossRefGoogle Scholar
  6. [6]
    M. J. Feng, S. W. Mao, T. Jiang. BOOST: Base station on-off switching strategy for energy efficient massive MIMO HetNets [C]//35th Annual IEEE International Conference on Computer Communications, San Francisco, 2016: 1–9.Google Scholar
  7. [7]
    Y. X. Zhu, L. F. Wang, K. K. Wong, et al. Wireless power transfer in massive MIMO-aided HetNets with user association [J]. IEEE Transactions on Communications, 2016, 64(10): 4181–4195.Google Scholar
  8. [8]
    J. Chen, H. B. Chen, H. Zhang, et al. Spectral-energy efficiency tradeoff in relay-aided massive MIMO cellular networks with pilot contamination [J]. IEEE Access, 2016, 4: 5234–5242.CrossRefGoogle Scholar
  9. [9]
    A. Q. He, L. F. Wang, Y. Chen, et al. Spectral and energy efficiency of uplink D2D underlaid massive MIMO cellular networks [J]. IEEE Transactions on Communications, 2017, 65(9): 3780–3793.CrossRefGoogle Scholar
  10. [10]
    W. Xu, J. Liu, S. Jin, et al. Spectral and energy efficiency of multipair massive MIMO relay network with hybrid processing [J]. IEEE Transactions on Communications, 2017, 65(9): 3794–3809.CrossRefGoogle Scholar
  11. [11]
    D. T. Liu, L. F. Wang, Y. Chen, et al. Distributed energy efficient fair user association in massive MIMO enabled HetNets [J]. IEEE Communications Letters, 2015, 19(10): 1770–1773.CrossRefGoogle Scholar
  12. [12]
    D. Bethanabhotla, O. Y. Bursalioglu, H. C. Papadopoulos, et al. Optimal user-cell association for massive MIMO wireless networks [J]. IEEE Transactions on Wireless Communications, 2016, 15(3): 1835–1850.CrossRefGoogle Scholar
  13. [13]
    A. Q. He, L. F. Wang, M. Elkashlan, et al. Spectrum and energy efficiency in massive MIMO enabled HetNets: A stochastic geometry approach [J]. IEEE Communications Letters, 2015, 19(12): 2294–2297.CrossRefGoogle Scholar
  14. [14]
    Y. Lin, Y. Wang, C. G. Li, et al. Energy efficient joint user association and power allocation design in massive MIMO empowered dense HetNets [C]//IEEE 84th Vehicular Technology Conference, Montreal, 2016: 1–6.Google Scholar
  15. [15]
    Y. Y. Hao, Q. Ni, H. Li, et al. Energy and spectral efficiency tradeoff with user association and power coordination in massive MIMO enabled HetNets [J]. IEEE Communications Letters, 2016, 20(10): 2091–2094.CrossRefGoogle Scholar
  16. [16]
    E. Bjornson, L. Sanguinetti, J. Hoydis, et al. Designing multi-user MIMO for energy efficiency: when is massive MIMO the answer [C]//IEEE Wireless Communications and Networking Conference, Istanbul, 2014: 242–247.Google Scholar
  17. [17]
    S. W. Huang, H. B. Chen, J. Cai, et al. Energy efficiency and spectralefficiency tradeoff in amplify-and-forward relay networks [J]. IEEE Transactions on Vehicular Technology, 2013, 62(9): 4366–4378.CrossRefGoogle Scholar
  18. [18]
    C. S. Zhang, J. H. Ge, J. Li, et al. Energy efficiency and spectral efficiency tradeoff for asymmetric two-way AF relaying with statistical CSI [J]. IEEE Transactions on Vehicular Technology, 2016, 65(4): 2833–2839.CrossRefGoogle Scholar
  19. [19]
    A. Garcia-Saavedra, P. Serrano, A. Banchs, et al. Energy-efficient fair channel access for IEEE 802.11 WLANs [C]//IEEE International Symposium on World of Wireless, Mobile and Multimedia Networks, Lucca, 2011: 1–9.Google Scholar
  20. [20]
    J. Nocedal, S Wright. Numerical optimization [M]. New York: Springer, 2006.MATHGoogle Scholar

Copyright information

© Posts & Telecom Press and Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Key Laboratory of Cognitive Radio and Information ProcessingGuilin University of Electronic TechnologyGuilinChina

Personalised recommendations