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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Liu, D., et al.: User association in 5G networks: a survey and an outlook. IEEE Commun. Surv. Tutor. 18(2), 1018–1044 (2016)
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)
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)
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)
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)
Shen, K., Yu, W.: Distributed pricing-based user association for downlink heterogeneous cellular networks. IEEE J. Sel. Areas Commun. 32(6), 1100–1113 (2014)
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)
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)
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)
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)
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)
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)
Acknowledgements
This work was funded by the Fundamental Research Funds for the Central Universities of China under grant no. PA2019GDQT0012.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Fang, C., Wang, L., Lin, H., Peng, M. (2020). A Generic Polynomial-Time Cell Association Scheme in Ultra-Dense Cellular Networks. In: Gao, H., Feng, Z., Yu, J., Wu, J. (eds) Communications and Networking. ChinaCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-030-41114-5_31
Download citation
DOI: https://doi.org/10.1007/978-3-030-41114-5_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-41113-8
Online ISBN: 978-3-030-41114-5
eBook Packages: Computer ScienceComputer Science (R0)