Collaborative Caching in Vehicular Edge Network Assisted by Cell-Free Massive MIMO

WANG Chaowei; WANG Ziye; XU Lexi; YU Xiaofei; ZHANG Zhi; WANG Weidong

doi:10.23919/cje.2022.00.294

Volume 32 Issue 6

Nov. 2023

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Article Navigation > Chinese Journal of Electronics > 2023 > 32(6): 1218-1229

WANG Chaowei, WANG Ziye, XU Lexi, et al., “Collaborative Caching in Vehicular Edge Network Assisted by Cell-Free Massive MIMO,” Chinese Journal of Electronics, vol. 32, no. 6, pp. 1218-1229, 2023, doi: 10.23919/cje.2022.00.294

Citation:

WANG Chaowei, WANG Ziye, XU Lexi, et al., “Collaborative Caching in Vehicular Edge Network Assisted by Cell-Free Massive MIMO,” Chinese Journal of Electronics, vol. 32, no. 6, pp. 1218-1229, 2023, doi: 10.23919/cje.2022.00.294

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Collaborative Caching in Vehicular Edge Network Assisted by Cell-Free Massive MIMO

doi: 10.23919/cje.2022.00.294

WANG Chaowei^{1, 2
,},
WANG Ziye^1
,,
XU Lexi^3
,,
YU Xiaofei^1
,,
ZHANG Zhi^4
,,
WANG Weidong^1
,

1.
School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
2.
Shaanxi Key Laboratory of Information Communication Network and Security,Xi’an University of Posts and Telecommunications, Xi’an 710121, China
3.
Research Institute, China United Network Communications Corporation, Beijing 100048, China
4.
School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China

Funds: This work was supported by the National Key R&D Program of China (2020YFB1807204)

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Author Bio:
Chaowei WANG was born in Sichuan Province in 1982. He received the Ph.D. degree from Beijing University of Posts and Telecommunications in 2010. He is currently an Associate Professor at the School of Electronic Engineering, Beijing University of Posts and Telecommunications. His research interests include wireless communications and IoT applications. (Email: wangchaowei@bupt.edu.cn)

Ziye WANG (corresponding author) received the B.S. degree in optoelectronic information science and engineering from Beijing University of Posts and Telecommunications in 2021, and she is currently pursuing the M.S. degree in electronics science and technology from Beijing University of Posts and Telecommunications. Her research interests include Internet of vehicles and mobile edge computing. (Email: wzy11140@bupt.edu.cn)

Lexi XU received the M.S. and Ph.D. degrees from Beijing University of Posts and Telecommunications, Beijing, China, and Queen Mary University of London, London, United Kingdom, in 2009 and 2013, respectively. He is a Senior Engineer at China Unicom and a China Unicom Delegate in ITU, ETSI, CCSA. His research interests include big data, self-organizing networks, satellite systems, radio resource management in communication systems. (Email: xulx29@chinaunicom.cn)

Xiaofei YU received the B.S. degree in electronics science and technology from Beijing University of Posts and Telecommunications, China, in 2018, and she is currently pursuing the Ph.D. degrees in electronics science and technology from Beijing University of Posts and Telecommunications. Her research interests include mobile edge computing and wireless communication. (Email: yuxiaofei@bupt.edu.cn)

Zhi ZHANG received the B.S. and Ph.D. degrees from Beijing University of Posts and Telecommunications, Beijing, China, in 1999 and 2004, respectively. He is currently a Professor and the Ph.D. Supervisor with the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications. His research interests include key technology of mobile communications, digital signal processing, and communication system design. (Email:zhangzhi@bupt.edu.cn)

Weidong WANG was born in Inner Mongolia Autonomous Region in 1967. He received the Ph.D. degree from Beijing University of Posts and Telecommunications in 2002. He is currently a Full Professor of School of Electronic Engineering at Beijing University of Posts and Telecommunications. His research interests include communication system, radio resource management, IOT, and signal processing. (Email: wangweidong@bupt.edu.cn)
Received Date: 2022-08-30
Accepted Date: 2023-02-07

Available Online: 2023-04-21

Publish Date: 2023-11-05

Abstract

Abstract

The 6G mobile communications demand lower content delivery latency and higher quality of service for vehicular edge network. With the popularity of content-centric networks, mobile users are paying more and more attention to the delay and reliability of fetching cached content. For reducing communication costs, increasing network capacity and improving the content delivery, we propose a collaborative caching scheme based on deep reinforcement learning for vehicular edge network assisted by cell-free massive multiple-input multiple-output (MIMO) system, in which the macro base station is considered as the central processor unit, and the roadside units are treated as roadside access points (RSAPs). The proposed scheme can effectively cache contents in edge nodes, i.e., RSAPs and vehicles with caching capability. We jointly consider the mobility of vehicles and the content request preferences of users, then we use deep Q-networks algorithm to optimize the caching decisions. Simulation results show that the proposed scheme can significantly reduce the content delivery average latency and increase the content cache hit ratio.
- Vehicular edge network,
- Cell-free massive MIMO,
- Collaborative caching,
- Content delivery latency,
- Deep reinforcement learning,
- Cache hit ratio

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References(45)

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