@inproceedings{da8f589235e64be8ae7f4c8fa94297ed,
title = "Distributed edge caching via reinforcement learning in fog radio access networks",
abstract = "In this paper, the distributed edge caching problem in fog radio access networks (F-RANs) is investigated. By considering the unknown spatio-temporal content popularity and user preference, a user request model based on hidden Markov process is proposed to characterize the fluctuant spatio-temporal traffic demands in F-RANs. Then, the Q-learning method based on the reinforcement learning (RL) framework is put forth to seek the optimal caching policy in a distributed manner, which enables fog access points (F-APs) to learn and track the potential dynamic process without extra communications cost. Furthermore, we propose a more efficient Q-learning method with value function approximation (Q-VFA-learning) to reduce complexity and accelerate convergence. Simulation results show that the performance of our proposed method is superior to those of the traditional methods.",
keywords = "Content popularity, Distributed edge caching, Fog radio access networks, Q-learning, User preference",
author = "Liuyang Lu and Yanxiang Jiang and Mehdi Bennis and Zhiguo Ding and Zheng, \{Fu Chun\} and Xiaohu You",
note = "Funding Information: This work was supported in part by the Natural Science Foundation of China under Grant 61521061, the Natural Science Foundation of Jiangsu Province under grant BK20181264, the Research Fund of the State Key Laboratory of Integrated Services Networks (Xidian University) under grant ISN19-10, the Research Fund of the Key Laboratory of Wireless Sensor Network \& Communication (Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences) under grant 2017002, the National Basic Research Program of China (973 Program) under grant 2012CB316004, and the U.K. Engineering and Physical Sciences Research Council under Grant EP/K040685/2. Publisher Copyright: {\textcopyright} 2019 IEEE.; 89th IEEE Vehicular Technology Conference, VTC Spring 2019 ; Conference date: 28-04-2019 Through 01-05-2019",
year = "2019",
month = apr,
doi = "10.1109/VTCSpring.2019.8746321",
language = "British English",
series = "IEEE Vehicular Technology Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings",
address = "United States",
}