Skip to main content

Advertisement

SpringerLink
Log in

Stackelberg game-based energy-efficient resource allocation for 5G cellular networks

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

Abstract

To obtain better bandwidth and performance, the fifth generation (5G) cellular network is proposed to implement new-generation cellular mobile communications for new applications such as the internet of things, big data, smart city and so on. However, due to multiple/dense cellular network structures and high data rate, the 5G cellular network holds high inter-cell interference (ICI) and lower energy efficiency. The soft frequency reuse (SFR) is introduced to reduce the inter-cell interference in multiple cellular networks (such as 5G cellular networks) with the orthogonal frequency division multiplexing in base stations. Then, we investigate the energy-efficient resource allocation problem in the 5G cellular network with SFR. To coordinate the ICI among adjacent cells, we introduce the interference pricing factor into the utility function. The energy-efficient resource allocation problem is described as a Stackelberg game model. Because the sub-carrier assignment in the optimization process is an integer program which is very hard to be solved, we make a relaxation for the integer variable in the model and propose an iteration algorithm to obtain the Stackelberg game equilibrium solution. Simulation results show that the proposed method is feasible and promising.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Ge, X., Jing, Y., Gharavi, H., et al. (2017). Energy efficiency challenges of 5G small cell networks. IEEE Communications Magazine, 55(5), 184–191.

    Article  Google Scholar 

  2. Yang, K., Martin, S., Quadri, D., et al. (2017). Energy-efficient downlink resource allocation in heterogeneous OFDMA networks. IEEE Transactions on Vehicular Technology, 66(6), 5086–5098.

    Article  Google Scholar 

  3. Tören, O., Ayduslu, E., Aydın, Y., et al. (2017). A novel hybrid OFDM technique for 5G. In Proceeding of the TSP’17 (pp. 195–199).

  4. Zappone, A., & Jorswieck, E. (2017). Energy-efficient resource allocation in future wireless networks by sequential fractional programming. Digital Signal Processing, 60, 324–337.

    Article  Google Scholar 

  5. Nawaz, S., Hassan, S., Zaidi, S., et al. (2016). Throughput and energy efficiency of two-tier cellular networks: Massive MIMO overlay for small cells. In Proceeding of the IWCMC’16 (pp. 874–879).

  6. Sun, Y., Xia, W., Zhang, S., et al. (2018). Energy efficient pico cell range expansion and density joint optimization for heterogeneous networks with eICIC. Sensors, 18(3), 762–780.

    Article  Google Scholar 

  7. Al-Zahrani, A., & Yu, F. (2016). An energy-efficient resource allocation and interference management scheme in green heterogeneous networks using game theory. IEEE Transactions on Vehicular Technology, 65(7), 5384–5396.

    Article  Google Scholar 

  8. Lam, S., & Sandrasegaran, K. (2016). Analytical coverage probability of a typical user in heterogeneous cellular networks. Journal of Networks, 11(12), 56–61.

    Google Scholar 

  9. Xu, L., Mao, Y., Leng, S., et al. (2017). Energy-efficient resource allocation strategy in ultra dense small-cell networks: A Stackelberg game approach. In Proceeding of the ICC’17 (pp. 1–6).

  10. Mwashita, W., & Odhiambo, M. O. (2017). Base station energy efficiency improvement for next generation mobile networks. International Journal of Electronics and Telecommunications, 63(2), 187–194.

    Article  Google Scholar 

  11. Yue, X., Liu, Y., Kang, S., et al. (2018). Exploiting full/half-duplex user relaying in NOMA systems. IEEE Transactions on Communications, 66(2), 560–575.

    Article  Google Scholar 

  12. Huo, L., Jiang, D., & Lv, Z. (2017). Soft frequency reuse-based optimization algorithm for energy efficiency of multi-cell networks. Computers and Electrical Engineering, 66, 1–16.

    Google Scholar 

  13. Coskun, C., Davaslioglu, K., & Ayanoglu, E. (2017). Three-stage resource allocation algorithm for energy-efficient heterogeneous networks. IEEE Transactions on Vehicular Technology, 66(8), 6942–6957.

    Article  Google Scholar 

  14. Ahmad, I., Feng, Z., Hameed, A., et al. (2014). Spectrum sharing and energy-efficient power optimization for two-tier femtocell networks. In Proceeding of the CROWNCOM’14 (pp. 156–161).

  15. Shen, K., & Yu, W. (2018). Fractional programming for communication systems—Part I: Power control and beamforming. IEEE Transactions on Signal Processing, 66(10), 2616–2630.

    Article  Google Scholar 

  16. Jiang, D., Wang, W., Shi, L., & Song, H. (2018). A compressive sensing-based approach to end-to-end network traffic reconstruction. IEEE Transactions on Network Science and Engineering. https://doi.org/10.1109/TNSE.2018.2877597.

    Article  Google Scholar 

  17. Jiang, D., Huo, L., & Song, H. (2018). Rethinking behaviors and activities of base stations in mobile cellular networks based on big data analysis. IEEE Transactions on Network Science and Engineering, 1(1), 1–12.

    Article  Google Scholar 

  18. Jiang, D., Huo, L., & Li, Y. (2018). Fine-granularity inference and estimations to network traffic for SDN. Plos One, 13(5), 1–23.

    Google Scholar 

  19. Jiang, D., Huo, L., Lv, Z., et al. (2018). A joint multi-criteria utility-based network selection approach for vehicle-to-infrastructure networking. IEEE Transactions on Intelligent Transportation Systems, 99, 1–15.

    Google Scholar 

  20. Huang, J., Li, J., Zhao, L., et al. (2017). CoSFR: Coordinated soft frequency reuse for OFDMA-based multi-cell networks with non-uniform user distribution. Wireless Networks, 23(7), 2037–2050.

    Article  Google Scholar 

  21. Kumar, S., Kalyani, S., & Giridhar, K. (2016). Impact of sub-band correlation on SFR and comparison of FFR and SFR. IEEE Transactions on Wireless Communications, 15(8), 5156–5166.

    Article  Google Scholar 

  22. Chen, Q., Yu, G., Elmaghraby, H., et al. (2017). Embedding LTE-U within Wi-Fi bands for spectrum efficiency improvement. IEEE Network, 31(2), 72–79.

    Article  Google Scholar 

  23. Zhang, H., Liu, H., Cheng, J., et al. (2018). Downlink energy efficiency of power allocation and wireless backhaul bandwidth allocation in heterogeneous small cell networks. IEEE Transactions on Communications, 66(4), 1705–1716.

    Article  Google Scholar 

  24. Chen, Q., Yu, G., Yin, R., et al. (2016). Energy-efficient user association and resource allocation for multi-stream carrier aggregation. IEEE Transactions on Vehicular Technology, 65(8), 6366–6376.

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (No. 61571104), the Sichuan Science and Technology Program (No. 2018JY0539), the Key Projects of the Sichuan Provincial Education Department (No. 18ZA0219), the Fundamental Research Funds for the Central Universities (No. ZYGX2017KYQD170), and the Innovation Funding (No. 2018510007000134). The authors wish to thank the reviewers for their helpful comments.

Author information

Authors and Affiliations

  1. College of Computer Science and Engineering, Northeastern University, Shenyang, 110819, China

    Liuwei Huo

  2. School of Astronautics and Aeronautic, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Dingde Jiang

Authors
  1. Liuwei Huo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dingde Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dingde Jiang.

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

Huo, L., Jiang, D. Stackelberg game-based energy-efficient resource allocation for 5G cellular networks. Telecommun Syst 72, 377–388 (2019). https://doi.org/10.1007/s11235-019-00564-w

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11235-019-00564-w

Keywords

Search

Navigation