Energy Efficient Handover for Heterogeneous Networks: A Non-Cooperative Game Theoretic Approach | Wireless Personal Communications Skip to main content

Advertisement

Springer Nature Link
Log in

Energy Efficient Handover for Heterogeneous Networks: A Non-Cooperative Game Theoretic Approach

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The small cell technology is considered as a key technology for 5G networks. The capacity expansion and coverage extension are both achieved through this deployment. However, the ultra-dense small cells deployment can cause a severe interference, a high number of frequent unnecessary handovers and/or handover failure and hence, high power consumption is expected due to the signalling overhead. Placing some small cells into idle mode, without causing degradation to the quality of service, is a good strategy to enhance the energy efficiency in the network. In this paper, we propose an energy efficient game theoretical method to reduce the energy consumption in dense small cells network. The proposed method enables the small cells to adjust their transmitting power while considering to balance the load among themselves. A non-cooperative game is formulated among the cells in the network to solve the cost function which considers both the power mode and its load. The game is solved using the regret matching-based learning distribution approach in which each cell chooses its optimal transmit power strategy to reach the equilibrium. The cell selection for handover is then made using a multiple attribute TOPSIS technique. Results show that the proposed method significantly reduces the power consumption and unnecessary handovers, in addition to improving the average small cell throughput compared to the conventional method.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Chu, X., Lopez-Perez, D., Yang, Y., & Gunnarsson, F. (2013). Heterogeneous Cellular Networks: Theory., Simulation and Deployment Cambridge: Cambridge University Press.

    Book  Google Scholar 

  2. Xu, P., Fang, X., He, R., & Xiang, Z. (2013). An efficient handoff algorithm based on received signal strength and wireless transmission loss in hierarchical cell networks. Telecommunication Systems, 52, 317–325.

    Article  Google Scholar 

  3. Singoria, R., Oliveira, T., & Agrawal, D. P. (2011). Reducing unnecessary handovers: Call admission control mechanism between wimax and femtocells. In Global telecommunications conference (GLOBECOM 2011) (pp. 1–5) IEEE.

  4. Alhabo, M., & Zhang, L. (2017). Unnecessary handover minimization in two-tier heterogeneous networks. In 13th annual conference on wireless on-demand network systems and services (WONS) (pp. 160–164), IEEE.

  5. Alhabo, M., Zhang, L., & Nawaz, N. (2017). A trade-off between unnecessary handover and handover failure for heterogeneous networks. In Proceedings of 23th European wireless conference, VDE.

  6. Alhabo, M., Zhang, L., & Oguejiofor, O. (2017). Inbound handover interference-based margin for load balancing in heterogeneous networks. In International symposium on wireless communication systems (ISWCS) (pp. 1-6), IEEE.

  7. Habibzadeh, A., Moghaddam, S. S., Razavizadeh, S. M., & Shirvanimoghaddam, M. (2017). Modeling and analysis of traffic-aware spectrum handover schemes in cognitive hetnets. Transactions on Emerging Telecommunications Technologies, 28(12), e3199.

    Article  Google Scholar 

  8. Habibzadeh, A., Moghaddam, S. S., Razavizadeh, S. M., & Shirvanimoghaddam, M. (2017). Analysis and performance evaluation of an efficient handover algorithm for cognitive hetnets. International Journal of Communication Systems, 30(16), e3315.

    Article  Google Scholar 

  9. Habibzadeh, A., Moghaddam, S. S., Razavizadeh, S., & Shirvanimoghaddam, M. (). A spectrum handover mechanism for secondary users in cognitive femtocell hetnets. In 24th Iranian conference on electrical engineering (ICEE) (pp. 442–446), IEEE.

  10. Habibzadeh, A., Moghaddam, S. S., Razavizadeh, S. M., & Shirvanimoghaddam, M. (2015). A novel handover decision-making algorithm for hetnets. In International symposium on signal processing and information technology (ISSPIT) (pp. 438–442), IEEE.

  11. Son, K., Kim, H., Yi, Y., & Krishnamachari, B. (2011). Base station operation and user association mechanisms for energy-delay tradeoffs in green cellular networks. IEEE Journal on Selected Areas in Communications, 29(8), 1525–1536.

    Article  Google Scholar 

  12. Oh, E., Krishnamachari, B., Liu, X., & Niu, Z. (2011). Toward dynamic energy-efficient operation of cellular network infrastructure. IEEE Communications Magazine, 49(6), 63.

    Article  Google Scholar 

  13. Yildiz, A., Girici, T., & Yanikomeroglu, H. (2013). A pricing based algorithm for cell switching off in green cellular networks. In 77th vehicular technology conference (VTC Spring) (pp. 1–6), IEEE.

  14. Merwaday, A., & Güvenç, I. (2016). Optimisation of feicic for energy efficiency and spectrum efficiency in lte-advanced hetnets. Electronics Letters, 52(11), 982–984.

    Article  Google Scholar 

  15. Alhabo, M., Zhang, L., & Nawaz, N. (2019). Gra-based handover for dense small cells heterogeneous networks. IET Communications, 13, 1928–1935.

    Article  Google Scholar 

  16. Li, Y., Zhang, H., Wang, J., Cao, B., Liu, Q., & Daneshmand, M. (2019). Energy-efficient deployment and adaptive sleeping in heterogeneous cellular networks. IEEE Access, 7, 35838–35850.

    Article  Google Scholar 

  17. Fang, F., Cheng, J., & Ding, Z. (2019). Joint energy efficient subchannel and power optimization for a downlink noma heterogeneous network. IEEE Transactions on Vehicular Technology, 68(2), 1351–1364.

    Article  Google Scholar 

  18. Yang, C., Li, J., Anpalagan, A., & Guizani, M. (2015). Joint power coordination for spectral-and-energy efficiency in heterogeneous small cell networks: A bargaining game-theoretic perspective. IEEE Transactions on Wireless Communications, 15(2), 1364–1376.

    Article  Google Scholar 

  19. Huang, X., Xu, W., Shen, H., Zhang, H., & You, X. (2018). Utility-energy efficiency oriented user association with power control in heterogeneous networks. IEEE Wireless Communications Letters, 7(4), 526–529.

    Article  Google Scholar 

  20. Tao, R., Liu, W., Chu, X., & Zhang, J. (2019). An energy saving small cell sleeping mechanism with cell range expansion in heterogeneous networks. IEEE Transactions on Wireless Communications, 2, 1933.

    Google Scholar 

  21. Zhang, J., & De la Roche, G. (2011). Femtocells: Technologies and Deployment. New York: Wiley.

    Google Scholar 

  22. Europe, Q. (2007). Hnb and hnb-macro propagation models, 3GPP R4- 071617.

  23. Auer, G., Giannini, V., Desset, C., Godor, I., Skillermark, P., Olsson, M., et al. (2011). How much energy is needed to run a wireless network? IEEE Wireless Communications, 18(5), 25.

    Article  Google Scholar 

  24. Protopopescu, D. (2010). Nash equilibrium strategies in discrete-time finite-horizon dynamic games with risk and effort-averse players.

  25. Aumann, R. (2010). Subjectivity and correlation in randomized strategies David K. Levine, Technical Report

  26. Lasaulce, S., & Tembine, H. (2011). Game Theory and Learning for Wireless Networks: Fundamentals and Applications. London: Academic Press.

    Google Scholar 

  27. Samarakoon, S., Bennis, M., Saad, W., & Latva-Aho, M. (2014). Opportunistic sleep mode strategies in wireless small cell networks. In International conference on communications (ICC) (pp. 2707–2712), IEEE.

  28. Alhabo, M., & Zhang, L. (2018). Multi-criteria handover using modified weighted topsis methods for heterogeneous networks. IEEE Access, 16, 40547–40558.

    Article  Google Scholar 

  29. Mehbodniya, A., Kaleem, F., Yen, K. K., & Adachi, F. (2013). Wireless network access selection scheme for heterogeneous multimedia traffic. IET Networks, 2(4), 214–223.

    Article  Google Scholar 

  30. Wang, Y.-M., & Luo, Y. (2010). Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making. Mathematical and Computer Modelling, 51(1), 1–12.

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Informatics and Telecommunication Public Company/Iraqi Ministry of Communications, Mosul, Iraq

    Mohanad Alhabo

  2. School of Electronic and Electrical Engineering, University of Leeds, Leeds, UK

    Li Zhang

  3. University of Engineering and Technology, Lahore, Pakistan

    Naveed Nawaz

Authors
  1. Mohanad Alhabo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Li Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Naveed Nawaz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohanad Alhabo.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Alhabo, M., Zhang, L. & Nawaz, N. Energy Efficient Handover for Heterogeneous Networks: A Non-Cooperative Game Theoretic Approach. Wireless Pers Commun 122, 2113–2129 (2022). https://doi.org/10.1007/s11277-021-08983-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-021-08983-2

Keywords

Search

Navigation