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Semantic Communication-Based Dynamic Resource Allocation in D2D Vehicular Networks

Authors :
Su, Jiawei
Liu, Zhixin
Xie, Yuan-ai
Ma, Kai
Du, Hongyang
Kang, Jiawen
Niyato, Dusit
Source :
IEEE Transactions on Vehicular Technology; August 2023, Vol. 72 Issue: 8 p10784-10796, 13p
Publication Year :
2023

Abstract

The semantic communication mechanism enables wireless devices in vehicular networks to communicate more effectively with the semantic meaning. However, in high-dynamic vehicular networks, the transmission of semantic information faces challenges in terms of reliability and stability. To address these challenges, a long-term robust resource allocation scheme is proposed under the Device-to-Device (D2D) vehicular (D2D-V) networks, where multiple performance indicators (user satisfaction, queue stability, and communication delay) are considered. Due to the sophisticated probabilistic form with consideration of channel fluctuations, the Bernstein approximation is introduced to acquire the deterministic constraint more efficiently. The robust resource allocation problem is proposed and separated into two independent subproblems by the Lyapunov optimization method, which includes semantic access control in the application layer and power control in the physical layer. After that, the successive convex approximation method and Karush-Kuhn-Tucher conditions are adopted to solve the subproblems, thereby proposing a robust resource allocation algorithm. The simulations reveal the trade-off relationship between user satisfaction, queue stability, and communication delay, which is on the premise of meeting the user SINR requirement. Moreover, the simulations also prove the necessity of considering channel uncertainty in high-speed mobile vehicular communication scenarios.

Details

Language :
English
ISSN :
00189545
Volume :
72
Issue :
8
Database :
Supplemental Index
Journal :
IEEE Transactions on Vehicular Technology
Publication Type :
Periodical
Accession number :
ejs63836691
Full Text :
https://doi.org/10.1109/TVT.2023.3257770