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Learning-Based Joint User-AP Association and Resource Allocation in Ultra Dense Network
- Publication Year :
- 2020
-
Abstract
- With the advantages of Millimeter wave in wireless communication network, the coverage radius and inter-site distance can be further reduced, the ultra dense network (UDN) becomes the mainstream of future networks. The main challenge faced by UDN is the serious inter-site interference, which needs to be carefully addressed by joint user association and resource allocation methods. In this paper, we propose a multi-agent Q-learning based method to jointly optimize the user association and resource allocation in UDN. The deep Q-network is applied to guarantee the convergence of the proposed method. Simulation results reveal the effectiveness of the proposed method and different performances under different simulation parameters are evaluated.<br />Comment: 5 pages, 5 figures
- Subjects :
- Computer Science - Networking and Internet Architecture
H.4.3
Subjects
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2004.08194
- Document Type :
- Working Paper