Joint Computation Offloading and Resource Allocation Strategy in ISAC-Assisted V2X Networks Based on MEC
Qian Liu, Sihong Wang, Qilie Liu, Zhi Qi · 2023
As Integrated Sensing and Communications (ISAC) technology iterates and evolves, it combines radar sensing with data communications to improve Service Quality and reduce latency. It shows great potential in many application scenarios requiring the ultra-large volume of sensing information, ultra-low latency, and high accuracy. This paper investigates the joint Resource Management and Computational Offloading problem in MEC-based V2X networks assisted by ISAC. Firstly, The joint optimization problem is framed as a task of maximizing system throughput, while adhering to constraints related to prolonged queuing delays and energy usage for individual tasks. Then, we transform the above constraints into a queueing stability problem by the Lyapunov method. Finally, we propose a Markov Decision Process (MDP) model and the joint Resource Management and Computational Offloading (DRMCO) algorithm based on Double-Depth Q-Networks (DDQNs). The final simulation results demonstrate that the proposed ISAC-assisted MEC vehicular network can achieve higher throughput than the conventional network compared to the benchmark scheme.