University of Oulu

Q. Chang, Y. Jiang, F. -C. Zheng, M. Bennis and X. You, "Cooperative Edge Caching via Multi Agent Reinforcement Learning in Fog Radio Access Networks," ICC 2022 - IEEE International Conference on Communications, Seoul, Korea, Republic of, 2022, pp. 3641-3646, doi: 10.1109/ICC45855.2022.9838588

Cooperative edge caching via multi agent reinforcement learning in fog radio access networks

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Author: Chang, Qi1; Jiang, Yanxiang1,2; Zheng, Fu-Chun1,2;
Organizations: 1National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
2School of Electronic and Information Engineering, Harbin Institute of Technology, Shenzhen, China
3Centre for Wireless Communications, University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 7 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2023-02-10


In this paper, the cooperative edge caching problem in fog radio access networks (F-RANs) is investigated. To minimize the content transmission delay, we formulate the cooperative caching optimization problem to find the globally optimal caching strategy. By considering the non-deterministic polynomial hard (NP-hard) property of this problem, a Multi Agent Reinforcement Learning (MARL)-based cooperative caching scheme is proposed. Our proposed scheme applies a double deep Q-network (DDQN) in every fog access point (F-AP), and introduces the communication process in a multi-agent system. Every F-AP records the historical caching strategies of its associated F-APs as the observations of communication procedure. By exchanging the observations, F-APs can leverage the cooperation and make the globally optimal caching strategy. Simulation results show that the proposed MARL-based cooperative caching scheme has remarkable performance compared with the benchmark schemes in minimizing the content transmission delay.

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Series: IEEE International Conference on Communications
ISSN: 1550-3607
ISSN-E: 1938-1883
ISSN-L: 1550-3607
ISBN: 978-1-5386-8347-7
ISBN Print: 978-1-5386-8348-4
Pages: 3641 - 3646
DOI: 10.1109/icc45855.2022.9838588
Host publication: ICC 2022 - IEEE International Conference on Communications
Conference: IEEE International Conference on Communications
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work was supported in part by the National Key Research and Development Program under Gran2021YFB2900300, the National Natural Science Foundation of China under grant 61971129, and the Shenzhen Science and Technology Program under Grant KQTD20190929172545139.
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