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On-line Access: 2022-01-24

Received: 2021-06-30

Revision Accepted: 2022-04-22

Crosschecked: 2021-09-14

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Chenxi LIU


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Frontiers of Information Technology & Electronic Engineering  2022 Vol.23 No.1 P.73-85


Joint uplink and downlink resource allocation for low-latency mobile virtual reality delivery in fog radio access networks

Author(s):  Tian DANG, Chenxi LIU, Xiqing LIU, Shi YAN

Affiliation(s):  State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China

Corresponding email(s):   tiandang@bupt.edu.cn, chenxi.liu@bupt.edu.cn, liuxiqing@bupt.edu.cn, yanshi01@bupt.edu.cn

Key Words:  Virtual reality delivery, Fog radio access network (F-RAN), Round-trip latency, Resource allocation

Tian DANG, Chenxi LIU, Xiqing LIU, Shi YAN. Joint uplink and downlink resource allocation for low-latency mobile virtual reality delivery in fog radio access networks[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(1): 73-85.

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%A Tian DANG
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%A Shi YAN
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T1 - Joint uplink and downlink resource allocation for low-latency mobile virtual reality delivery in fog radio access networks
A1 - Tian DANG
A1 - Chenxi LIU
A1 - Xiqing LIU
A1 - Shi YAN
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 23
IS - 1
SP - 73
EP - 85
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2100308

Fog radio access networks (F-RANs), in which the fog access points are equipped with communication, caching, and computing functionalities, have been anticipated as a promising architecture for enabling virtual reality (VR) applications in wireless networks. Although extensive research efforts have been devoted to designing efficient resource allocation strategies for realizing successful mobile VR delivery in downlink, the equally important resource allocation problem of mobile VR delivery in uplink has so far drawn little attention. In this work, we investigate a mobile VR F-RAN delivery framework, where both the uplink and downlink transmissions are considered. We first characterize the round-trip latency of the system, which reveals its dependence on the communication, caching, and computation resource allocations. Based on this information, we propose a simple yet efficient algorithm to minimize the round-trip latency, while satisfying the practical constraints on caching, computation capability, and transmission capacity in the uplink and downlink. Numerical results show that our proposed algorithm can effectively reduce the round-trip latency compared with various baselines, and the impacts of communication, caching, and computing resources on latency performance are illustrated.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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