- Title
- Scheduling and power control for connectivity enhancement in multi-hop I2V/V2V networks
- Creator
- Nguyen, Bach; Ngo, Duy; Dao, Minh; Bao, Vo; Vu, Hai
- Date
- 2022
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/186566
- Identifier
- vital:16929
- Identifier
-
https://doi.org/10.1109/TITS.2021.3091130
- Identifier
- ISBN:1524-9050 (ISSN)
- Abstract
- Infrastructure-to-vehicle (I2V) and vehicle-to-vehicle (V2V) communications are often combined to extend the connectivity and coverage in the Intelligent Transportation System (ITS) and its applications, e.g., augmented reality, real-time parking management and online shopping. Through multi-hop I2V and V2V communications, requesting vehicles are always connected to road side units (RSUs) even when they do not reside within the RSUs' coverage range. However, there may be not adequate network resource for several I2V and V2V links when multiple vehicles request services simultaneously. In this paper, we propose a joint frequency scheduling and power control scheme to enhance connectivity in multi-hop I2V/V2V networks. We associate I2V and V2V links with tuple-links, then formulate an NP-hard problem in which a frequency scheduler and a power controller are jointly designed for the tuple-links. The NP-hard problem is decomposed into two separate subproblems by employing the delayed column generation technique. Then, we employ a method for linear programming and a greedy algorithm to address these subproblems. Through numerical experiments with practical parameter settings, we demonstrate the proposed scheme outperforms several existing ones in terms of connectivity enhancement, measured by the service resumption number and average achieved throughput. Furthermore, the efficiency of our scheme is further enhanced when the number of available channels is high, and buffer size equipped to the requesting vehicles is large. © 2000-2011 IEEE.
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Relation
- IEEE Transactions on Intelligent Transportation Systems Vol. 23, no. 8 (2022), p. 10322-10332
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2021 IEEE
- Subject
- 3509 Transportation, logistics and supply chains; 4602 Artificial intelligence; 4603 Computer vision and multimedia computation; Connectivity; Infrastructure-to-vehicle communications; Intelligent transportation systems; Multi-hop; Power control; Scheduling; Vehicle-to-vehicle communications
- Reviewed
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