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A Generic Polynomial-Time Cell Association Scheme in Ultra-Dense Cellular Networks

  • Chao Fang
  • Lusheng WangEmail author
  • Hai Lin
  • Min Peng
Conference paper
  • 183 Downloads
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 312)

Abstract

Cell association in heterogeneous cellular networks is a significant research issue, but existing schemes mainly optimize a single objective and could not solve such a problem with a generic utility function in polynomial time. This paper proposes a cell association scheme for generic optimization objectives with polynomial-time complexity, which employs a virtual base station method to transform it into a 2-dimensional assignment problem solved by Hungarian algorithm. Based on this scheme, a framework for the tradeoff among multiple optimization objectives is designed. This framework jointly considers spectral efficiency and load balancing, designs a weight factor to adjust their impacts on the optimization, and uses an experience pool to store the relationship between performance demands and corresponding weight factor values. For an instantaneous cell association decision in a given network scenario, the association results are obtained as soon as the corresponding factor value is taken from the pool and the Hungarian algorithm is called for the matching. Compared with existing schemes, our proposal achieves a better tradeoff between system capacity and UE fairness with an extremely low time cost.

Keywords

Heterogeneous cellular networks Cell association 2-dimensional assignment problem Hungarian algorithm Fairness 

Notes

Acknowledgements

This work was funded by the Fundamental Research Funds for the Central Universities of China under grant no. PA2019GDQT0012.

References

  1. 1.
    Liu, D., et al.: User association in 5G networks: a survey and an outlook. IEEE Commun. Surv. Tutor. 18(2), 1018–1044 (2016)CrossRefGoogle Scholar
  2. 2.
    Andrews, J., Claussen, H., Dohler, M., Rangan, S., Reed, M.: Femtocell: past, present, and future. IEEE J. Sel. Areas Commun. 30(3), 497–508 (2012)CrossRefGoogle Scholar
  3. 3.
    Andrews, J., Singh, S., Ye, Q., Lin, X., Dhillon, H.: An overview of load balancing in HetNets: old myths and open problems. IEEE Wirel. Commun. 21(2), 18–25 (2014)CrossRefGoogle Scholar
  4. 4.
    Ge, X., Li, X., Jin, H., Cheng, J., Leung, V.: Joint user association and user scheduling for load balancing in heterogeneous networks. IEEE Trans. Wirel. Commun. 17(5), 3211–3225 (2018)CrossRefGoogle Scholar
  5. 5.
    Sun, Y., Feng, G., Qin, S., Sun, S.: Cell association with user behavior awareness in heterogeneous cellular networks. IEEE Trans. Veh. Technol. 67(5), 4589–4601 (2018)CrossRefGoogle Scholar
  6. 6.
    Shen, K., Yu, W.: Distributed pricing-based user association for downlink heterogeneous cellular networks. IEEE J. Sel. Areas Commun. 32(6), 1100–1113 (2014)CrossRefGoogle Scholar
  7. 7.
    Qian, L., Wu, Y., Zhou, H., Shen, X.: Joint uplink base station association and power control for small-cell networks with non-orthogonal multiple access. IEEE Trans. Wirel. Commun. 16(9), 5567–5582 (2017)CrossRefGoogle Scholar
  8. 8.
    Li, Z., Wang, C., Jiang, C.: User association for load balancing in vehicular networks: an online reinforcement learning approach. IEEE Trans. Intell. Transp. Syst. 18(8), 2217–2228 (2017)CrossRefGoogle Scholar
  9. 9.
    Zhao, N., Liang, Y., Niyato, D., Pei, Y., Wu, M., Jiang, Y.: Deep reinforcement learning for user association and resource allocation in heterogeneous cellular networks. IEEE Trans. Wirel. Commun. (in press)Google Scholar
  10. 10.
    Wang, W., Wu, X., Xie, L., Lu, S.: Femto-matching: efficient traffic offloading in heterogeneous cellular networks. In: IEEE INFOCOM, pp. 325–333. IEEE, Hong Kong (2015)Google Scholar
  11. 11.
    Prasad, N., Arslan, M., Rangarajan, S.: Exploiting cell dormancy and load balancing in LTE HetNets: optimizing the proportional fairness utility. IEEE Trans. Commun. 62(10), 3706–3722 (2014)CrossRefGoogle Scholar
  12. 12.
    Mishra, S., Rangineni, S., Murthy, C.: Exploiting an optimal user association strategy for interference management in HetNets. IEEE Commun. Lett. 18(10), 1799–1802 (2014)CrossRefGoogle Scholar
  13. 13.

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020

Authors and Affiliations

  1. 1.Anhui Province Key Laboratory of Industry Safety and Emergency Technology, School of Computer Science and Information EngineeringHefei University of TechnologyHefeiChina
  2. 2.Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and EngineeringWuhan UniversityWuhanChina

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