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Infrastructure-Assisted on-Driving Experience Sharing for Millimeter-Wave Connected Vehicles

Authors
Jung, SoyiKim, JoongheonLevorato, MarcoCordeiro, CarlosKim, Jae-Hyun
Issue Date
8월-2021
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
CAPEX; Delays; OPEX; Optimization; RSU allocation; Relays; Resource management; Scheduling; Streaming media; V2V; Vehicle-to-everything; mmWave spectrum; scheduling
Citation
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, v.70, no.8, pp.7307 - 7321
Indexed
SCIE
SCOPUS
Journal Title
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume
70
Number
8
Start Page
7307
End Page
7321
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/137057
DOI
10.1109/TVT.2021.3094806
ISSN
0018-9545
Abstract
This paper proposes on-driving experience sharing algorithms at junctions in infrastructure-assisted vehicles-to-everything networks. For the purpose, a millimeter-wave (mmWave) technology is used because it provides multi-Gbps data rates which is helpful for handling users' short stay times at junctions and spatial reuse due to high beam directionality which is helpful for interference-avoidance among densely deployed vehicles at junctions. To realize on-driving experience sharing, the proposed algorithms focus on joint resource allocation and scheduling for 3GPP-compliant multiple unicast vehicle-to-vehicle (V2V) communications where the vehicles are group leaders (GLs) in 3GPP Mode 4(d). The resource allocation stands for the roadside unit (RSU) allocation to scheduled V2V GL links where RSU is essentially required for overcoming blockage by establishing two-hop relaying. Because vehicles stay for short times at junctions, this paper designs two algorithms without or with delay considerations. Without delay considerations, the joint optimization of RSU allocation and scheduling was originally formulated as mixed 0-1 non-convex optimization. However our proposed algorithm reformulates the problem into mixed 0-1 convex optimization, which is computationally easier to solve. With delay considerations, our proposed algorithm dynamically controls video contents frame rates for time-average on-driving video sharing quality maximization subject to delay constraints, inspired by Lyapunov optimization. Extensive simulation results demonstrate that our algorithms can significantly outperform in a variety of scenarios. Furthermore, we conduct the cost analysis for the proposed algorithms in terms of capital expenditure (CAPEX) and operating expenditure (OPEX).
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공과대학 (전기전자공학부)
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