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DOI number:10.1109/ICCC52777.2021.9580261
Affiliation of Author(s):School of ComputerScience and Information Engineering, Hefei University of Technology
Journal:2021 IEEE/CIC International Conference on Communications in China
Funded by:National Natural Science Foundation of China under Grants 61971176 and 61901156, Anhui Provincial Na
Key Words:D2D communication, resource allocation, user association, ultra-dense network, deep reinforcement learning.
Abstract:With the ultra-dense deployment of small-cell base stations (SBSs), it is common today to find a user locates within the coverage area of several SBSs. In this paper, we investigate the joint user association and resource allocation problem of D2D pairs in ultra-dense cellular networks. Specifically, we formulate an optimization problem for D2D pairs that are within the overlapping coverage areas of several SBSs. By jointing optimizing the user association and resource allocation of such D2D pairs, we maximize the overall data rate of both cellular users and D2D pairs. After that, the double-dueling-deep Qnetwork (D3QN) algorithm is adopted to address the formulated problem, in which we consider the central controller in the network as an agent, and let it interact with the environment to find the optimal user association and resource allocation strategy. Numerical results validate that our proposed D3QN algorithm could achieve near-optimal performance, and is superior to other schemes.
Co-author:Xiaowei, Meng,Linsheng, Mei,Wei, Huang
First Author:Caihong, Kai
Indexed by:Conference
Discipline:Engineering
Document Type:C
ISSN No.:2377-8644
Translation or Not:no
Date of Publication:2021-11-13
Included Journals:EI