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AuthorCheng, Zhipeng
AuthorChen, Ning
AuthorLiu, Bang
AuthorGao, Zhibin
AuthorHuang, Lianfen
AuthorDu, Xiaojiang
AuthorGuizani, Mohsen
Available date2022-11-27T13:01:00Z
Publication Date2020-08-04
Publication NameComputer Networks
Identifierhttp://dx.doi.org/10.1016/j.comnet.2020.107312
CitationCheng, Z., Chen, N., Liu, B., Gao, Z., Huang, L., Du, X., & Guizani, M. (2020). Joint user association and resource allocation in HetNets based on user mobility prediction. Computer Networks, 177, 107312.‏
ISSN13891286
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85085547223&origin=inward
URIhttp://hdl.handle.net/10576/36728
AbstractVirtual small cell (VSC) formed by directional beams is seen as an alternative for the small base station (SBS) within the coverage of macro base station (MBS), to increase system capacity and reduce site cost. However, the flexibility of development for VSC poses challenges to user association and resource allocation in heterogeneous networks. In this paper, we consider the joint problem of user association and resource allocation in VSC aided multi-tier heterogeneous networks. To better analyze the formation of VSC and the impact of user mobility on the system, a user mobility prediction model is firstly constructed based on the Markov model. Then the joint user association and resource allocation problem is formulated to maximize the system capacity. Since the aforementioned problem is a coupling problem, two different solutions, namely, a decoupling solution and a coupling solution, are proposed based on the multi-agent Q-learning (MAQL) method, to find the optimal user association and resource allocation strategy. Moreover, to overcome the state and action space explosion in MAQL and accelerate convergence, the deep Q-network (DQN) is applied. Simulation results reveal that the deployment of VSC can increase the system capacity and spectrum efficiency. The coupling solution achieves better performance than the decoupling solution under a large number of users.
SponsorThis work was supported by National Natural Science Foundation of China (Grant Number 61971365,61871339).
Languageen
PublisherElsevier B.V.
SubjectDeep Q-network
Heterogeneous networks
Multi-agent Q-learning
Resource allocation
User association
User mobility prediction
Virtual small cell
TitleJoint user association and resource allocation in HetNets based on user mobility prediction
TypeArticle
Volume Number177
dc.accessType Abstract Only


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