Game theoretic handover optimisation for dense small cells heterogeneous networks

Game theoretic handover optimisation for dense small cells heterogeneous networks

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In this study, the authors formulate a non-cooperative game approach in which all base stations compete in a selfish manner to transmit at higher power. Each base station in the network is considered as a player in the game. The solution of the game is obtained by finding the optimal point, namely the Nash equilibrium. The proposed method, named efficient handover game theoretic, targets to manage the handover in dense small cell heterogeneous networks. Each player in the game optimises its payoff by adjusting the transmission power so as to enhance the overall performance in terms of throughput, handover, energy consumption, and load balancing. In order to choose the preferred transmission power for each player, the payoff function takes into account the gain of increasing the transmission power, energy consumption, base station load, and unnecessary handover. The cell selection is performed using the technique for order preference by similarity to an ideal solution (TOPSIS). A game theoretical approach is implemented and evaluated for dense small cell heterogeneous networks to validate the enhancement achieved in the proposed method. Results show that the proposed game theoretical approach provides a throughput enhancement while reducing the power consumption in addition to minimise the unnecessary handover and balance the load between base stations.


    1. 1)
      • 1. Chu, X., Lopez-Perez, D., Yang, Y., et al: ‘Heterogeneous cellular networks: theory, simulation and deployment’ (Cambridge University Press, New York USA, 2013).
    2. 2)
      • 2. Singoria, R., Oliveira, T., Agrawal, D.P.: ‘Reducing unnecessary handovers: call admission control mechanism between WiMAX and femtocells’. 2011 IEEE Global Telecommunications Conf. (GLOBECOM 2011), Texas, USA, 2011, pp. 15.
    3. 3)
      • 3. Alhabo, M., Zhang, L.: ‘Unnecessary handover minimization in two-tier heterogeneous networks’. 2017 13th Annual Conf. on Wireless On-demand Network Systems and Services (WONS), Wyoming, USA, 2017, pp. 160164.
    4. 4)
      • 4. Alhabo, M., Zhang, L., Nawaz, N.: ‘A trade-off between unnecessary handover and handover failure for heterogeneous networks’. 23th European Wireless Conf. in Proc. of European Wireless 2017, VDE, Dresden, Germany, 2017, pp. 16.
    5. 5)
      • 5. Alhabo, M., Zhang, L., Oguejiofor, O.: ‘Inbound handover interference-based margin for load balancing in heterogeneous networks’. 2017 Int. Symp. on Wireless Communication Systems (ISWCS), Bologna, Italy, 2017, pp. 16.
    6. 6)
      • 6. Alhabo, M., Zhang, L.: ‘Load-dependent handover margin for throughput enhancement and load balancing in HetNets’, IEEE Access, 2018, 6, pp. 6771867731.
    7. 7)
      • 7. Alhabo, M., Zhang, L.: ‘Multi-criteria handover using modified weighted TOPSIS methods for heterogeneous networks’, IEEE Access, 2018, 6, pp. 4054740558.
    8. 8)
      • 8. Son, K., Kim, H., Yi, Y., et al: ‘Base station operation and user association mechanisms for energy-delay tradeoffs in green cellular networks’, IEEE J. Sel. Areas Commun., 2011, 29, (8), pp. 15251536.
    9. 9)
      • 9. Oh, E., Krishnamachari, B., Liu, X., et al: ‘Toward dynamic energy-efficient operation of cellular network infrastructure’, IEEE Commun. Mag., 2011, 49, (6), pp. 5661.
    10. 10)
      • 10. Yildiz, A., Girici, T., Yanikomeroglu, H.: ‘A pricing based algorithm for cell switching off in green cellular networks’. 2013 IEEE 77th Vehicular Technology Conf. (VTC Spring), Dresden, Germany, 2013, pp. 16.
    11. 11)
      • 11. Merwaday, A., Güvenç, I.: ‘Optimisation of FeICIC for energy efficiency and spectrum efficiency in LTE-advanced HetNets’, Electron. Lett., 2016, 52, (11), pp. 982984.
    12. 12)
      • 12. Alhabo, M., Zhang, L., Nawaz, N.: ‘GRA-based handover for dense small cells heterogeneous networks’, IET Commun., 2019, 68, pp. 13511364.
    13. 13)
      • 13. Fang, F., Cheng, J., Ding, Z.: ‘Joint energy efficient subchannel and power optimization for a downlink NOMA heterogeneous network’, IEEE Trans. Veh. Technol., 2019, 68, (2), pp. 13511364.
    14. 14)
      • 14. Li, Y., Zhang, H., Wang, J., et al: ‘Energy-efficient deployment and adaptive sleeping in heterogeneous cellular networks’, IEEE Access, 2019, 7, pp. 3583835850.
    15. 15)
      • 15. Huang, X., Xu, W., Shen, H., et al: ‘Utility-energy efficiency oriented user association with power control in heterogeneous networks’, IEEE Wirel. Commun. Lett., 2018, 7, (4), pp. 526529.
    16. 16)
      • 16. Yang, C., Li, J., Anpalagan, A., et al: ‘Joint power coordination for spectral-and-energy efficiency in heterogeneous small cell networks: a bargaining game-theoretic perspective’, IEEE Trans. Wirel. Commun., 2015, 15, (2), pp. 13641376.
    17. 17)
      • 17. Tao, R., Liu, W., Chu, X., et al: ‘An energy saving small cell sleeping mechanism with cell range expansion in heterogeneous networks’, IEEE Trans. Wirel. Commun., 2019, 18, (5), pp. 24512463.
    18. 18)
      • 18. Zhang, H., Ma, W., Li, W., et al: ‘Signalling cost evaluation of handover management schemes in LTE-advanced femtocell’. 2011 IEEE 73rd Vehicular Technology Conf. (VTC Spring), Yokohama, Japan, 2011, pp. 15.
    19. 19)
      • 19. Stüber, G.L.: ‘Principles of mobile communication’ (Springer Science & Business Media, New York, USA, 2011).
    20. 20)
      • 20. Nguyen-Vuong, Q.-T., Ghamri-Doudane, Y., Agoulmine, N.: ‘On utility models for access network selection in wireless heterogeneous networks’. 2008 Network Operations and Management Symp. (NOMS 2008), Salvador, Bahia, Brazil, 2008, pp. 144151.
    21. 21)
      • 21. Bulusu, N., Estrin, D., Girod, L., et al: ‘Scalable coordination for wireless sensor networks: self-configuring localization systems’. Int. Symp. on Communication Theory and Applications (ISCTA 2001), Ambleside, UK, 2001.
    22. 22)
      • 22. Nikaidô, H., Isoda, K.: ‘Note on non-cooperative convex game’, Pacific J. Math., 1955, 5, (5), pp. 807815.
    23. 23)
      • 23. Rosen, J.B.: ‘Existence and uniqueness of equilibrium points for concave n-person games’, Econometrica, 1965, 33, pp. 520534.
    24. 24)
      • 24. Kuhn, H., Tucker, A.: ‘Nonlinear programming’. Proc. Second Berkeley Symp. on Mathematical Statistics and Probability, Princeton university and stanford university, USA, 1951, pp. 481492.
    25. 25)
      • 25. Mehbodniya, A., Kaleem, F., Yen, K.K., et al: ‘Wireless network access selection scheme for heterogeneous multimedia traffic’, IET Netw., 2013, 2, (4), pp. 214223.
    26. 26)
      • 26. Wang, Y.-M., Luo, Y.: ‘Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making’, Math. Comput. Model., 2010, 51, (1), pp. 112.

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