Semantic-Aware Cooperative Communication and Computation Framework in Vehicular Networks
Semantic Communication (SC) combined with Vehicular edge computing (VEC) provides an efficient edge task processing paradigm for Internet of Vehicles (IoV). Focusing on highway scenarios, this paper proposes a Tripartite Cooperative Semantic Communication (TCSC) framework, which enables Vehicle Users (VUs) to perform semantic task offloading via Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) communications. Considering task latency and the number of semantic symbols, the framework constructs a Mixed-Integer Nonlinear Programming (MINLP) problem, which is transformed into two subproblems. First, we innovatively propose a multi-agent proximal policy optimization task offloading optimization method based on parametric distribution noise (MAPPO-PDN) to solve the optimization problem of the number of semantic symbols; second, linear programming (LP) is used to optimize the offloading ratio. Simulations show that performance of this scheme is superior to that of other algorithms.
Authors
- Kezhi Wang (ORCID: https://orcid.org/0000-0001-8602-0800)
- Qiong Wu (ORCID: https://orcid.org/0009-0005-7884-411X)
- Maoxin Ji
- Pingyi Fan
- Jingbo Zhang
- Wen Chen
Institutions
- Jiangnan University (CN)
- Shanghai Jiao Tong University (CN)
- Brunel University of London (GB)
- Middlesex University London (GB)
- Tsinghua University (CN)
Publication Details
- Journal
- IEEE Networking Letters
- Published
- 2025-12-25
- DOI
- https://doi.org/10.1109/lnet.2025.3648419
- Primary Topic
- Vehicular Ad Hoc Networks (VANETs)
- Type
- article
- Field-Weighted Citation Impact
- 0.00