Semantic communication-based dynamic resource allocation in D2D vehicular networks
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 thes...
| Main Authors: | , , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Online Access: | https://hdl.handle.net/10356/170820 |
| _version_ | 1811684250005536768 |
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| author | Su, Jiawei Liu, Zhixin Xie, Yuan-Ai Ma, Kai Du, Hongyang Kang, Jiawen Niyato, Dusit |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Su, Jiawei Liu, Zhixin Xie, Yuan-Ai Ma, Kai Du, Hongyang Kang, Jiawen Niyato, Dusit |
| author_sort | Su, Jiawei |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T04:25:38Z |
| format | Journal Article |
| id | ntu-10356/170820 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:25:38Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1708202023-10-03T06:14:23Z Semantic communication-based dynamic resource allocation in D2D vehicular networks Su, Jiawei Liu, Zhixin Xie, Yuan-Ai Ma, Kai Du, Hongyang Kang, Jiawen Niyato, Dusit School of Computer Science and Engineering Interdisciplinary Graduate School (IGS) Energy Research Institute @ NTU (ERI@N) Engineering::Computer science and engineering Lyapunov Optimization Resource Allocation 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. Info-communications Media Development Authority (IMDA) National Research Foundation (NRF) This work was supported in part by the National Natural Science Foundation of China under Grants 62273298 and 61873223, in part by the Graduate Innovation Foundation Projects of Hebei Province under Grant CXZZBS2023055, in part by the National Research Foundation Singapore and Infocomm Media Development Authority through the Future Communications Research Development Programme (FCP) under Grant FCP-NTU-RG-2022-010, and in part by DSO National Laboratories through the AI Singapore Programme AISG under Grant AISG2-RP-2020-019 through Energy Research Test-Bed and Industry Partnership Funding Initiative part of the Energy Grid (EG) 2.0 Programme. 2023-10-03T06:14:22Z 2023-10-03T06:14:22Z 2023 Journal Article Su, J., Liu, Z., Xie, Y., Ma, K., Du, H., Kang, J. & Niyato, D. (2023). Semantic communication-based dynamic resource allocation in D2D vehicular networks. IEEE Transactions On Vehicular Technology, 72(8), 10784-10796. https://dx.doi.org/10.1109/TVT.2023.3257770 0018-9545 https://hdl.handle.net/10356/170820 10.1109/TVT.2023.3257770 2-s2.0-85151551558 8 72 10784 10796 en FCP-NTU-RG-2022-010 AISG2-RP-2020-019 IEEE Transactions on Vehicular Technology © 2023 IEEE. All rights reserved. |
| spellingShingle | Engineering::Computer science and engineering Lyapunov Optimization Resource Allocation Su, Jiawei Liu, Zhixin Xie, Yuan-Ai Ma, Kai Du, Hongyang Kang, Jiawen Niyato, Dusit Semantic communication-based dynamic resource allocation in D2D vehicular networks |
| title | Semantic communication-based dynamic resource allocation in D2D vehicular networks |
| title_full | Semantic communication-based dynamic resource allocation in D2D vehicular networks |
| title_fullStr | Semantic communication-based dynamic resource allocation in D2D vehicular networks |
| title_full_unstemmed | Semantic communication-based dynamic resource allocation in D2D vehicular networks |
| title_short | Semantic communication-based dynamic resource allocation in D2D vehicular networks |
| title_sort | semantic communication based dynamic resource allocation in d2d vehicular networks |
| topic | Engineering::Computer science and engineering Lyapunov Optimization Resource Allocation |
| url | https://hdl.handle.net/10356/170820 |
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