Game-Theoretic Approach for Integrated Sensing and Computation Offloading in Vehicular Edge Networks: A Utility Maximization Design
Lina Wang, Weihong Wu, Minghui Dai, Haijun Zhang · IEEE Internet of Things Journal · 2025
In recent years, with the rapid development of the Internet of Vehicles (IoV) and the widespread application of integrated sensing and communication (ISAC) in the IoV, the integrated sensing and computation offloading in vehicular edge networks has attracted widespread attention from academia and industry. Due to the generation of a large number of latency-sensitive tasks from vehicles’ real-time sensing of road conditions, coupled with the rise of other computing-intensive vehicle applications, the current computing capabilities of the onboard devices cannot meet the diverse demands of vehicular users. Therefore, it is necessary to combine the computing resources around the vehicle to complete computing tasks. With the goal of maximizing the difference between gain and consumption, this article studies the integrated sensing and computation offloading involving roadside units (RSUs) and vehicle platoon in vehicular edge networks. Specifically, we first consider that mobile vehicles can simultaneously offload computing tasks to the RSU and the vehicle platoon via nonorthogonal multiple access (NOMA) technology, and construct a multiobjective optimization problem with the goal of maximizing the utility of the three parties. Then, we construct a game model among the ISAC vehicle, the RSU, and the vehicle platoon based on the Stackelberg game. By seeking the equilibrium of the game, the optimal offloading and pricing strategy are derived, while the utility of the three parties is maximized. Finally, the simulation results show that the proposed scheme is superior to other traditional schemes, and each party in the game obtains its optimal strategy.