Primary-secondary resource-management on vehicular networks under soft and hard collision constraints

In this paper, a primary-secondary resource-management controller on Vehicular Networks is designed and tested. We cast the resource-management problem into a suitable constrained stochastic Network Utility Maximization problem and derive the optimal cognitive resource management controller, which dynamically allocates the access time-windows at the primary users (the serving Roadside Units) and the access rates and traffic flows at the secondary users (the served Vehicular Clients). We provide the optimal mem-oryless controllers under hard and soft primary-secondary collision constraints, showing as the hard controller presents no optimality gap in the average utility with respect to the soft one. Finally we generalize the framework integrating the controllers with the data fusion techniques.