Dynamic Optimal Random Access for Vehicle-to-Roadside Communications

In a drive-thru scenario where vehicles drive by a roadside access point (AP) to obtain temporary Internet access, it is important to design efficient resource allocation schemes to fully utilize the limited communication opportunities. In this paper, we study the random access problem in drive thru communications in a dynamic environment, where both the channel contention level and channel capacity vary over time. We assume that a vehicle has a file to upload when it is within the coverage range of the AP. The vehicle will pay a fixed amount each time it tries to access the AP, and will incur a penalty if it cannot finish the file uploading when leaving the AP. We first formulate the optimal transmission problem as a finite-horizon sequential decision problem. Then we solve the problem using dynamic programming, and design a dynamic optimal random access algorithm. Simulation results based on a realistic vehicular traffic model show that our algorithm achieves the minimal total cost, the highest probability of completing file upload, and the highest upload ratio as compared with two other heuristic schemes.