Dynamic Resource Allocation in Queue-Constrained and Delay-Sensitive Vehicular Networks

Abstract

Since performing reliable and real-time data transmission is challenging, this paper focuses on the dynamic resource allocation framework with queue and delay constraints in vehicular relay networks, where vehicle users and roadside users are in cooperative communications. To reduce data fluctuation and tackle channel uncertainty, the Lyapunov optimization theory is integrated into the long-term dynamic resource allocation framework, which addresses multiple performance indicators including queue backlog, communication delay, and user utility. In particular, the hierarchical competitive relationship between vehicle users and roadside users is captured, and the Stackelberg game structure is adopted to maximize the utilities of all users. Furthermore, the lower-game subproblem is transformed by the Lyapunov optimization method and is solved by the Lagrangian function method. As the best response function, the lower-game solution is used to formulate the upper-game strategy. Since the existing of game equilibrium (GE) solution, a Stackelberg game-enabled robust resource allocation algorithm can be proposed. Finally, various numerical simulations are performed to show that the proposed algorithm has better robustness and higher throughout than the benchmarks.