Abstract
Anti-jamming games have become a popular research topic. However, there are not many publications devoted to such games in the case of vehicular ad hoc networks (VANETs). We considered a VANET anti-jamming game on the road using a realistic driving model. Further, we assumed the quadratic power function in both vehicle and jammer utility functions instead of the standard linear term. This makes the game model more realistic. Using mathematical methods, we expressed the Nash equilibrium through the system parameters in single-channel and multi-channel cases. Since the network parameters are usually unknown, we also compared the performance of several reinforcement learning algorithms that iteratively converge to the Nash equilibrium predicted analytically without having any information about the environment in the static and dynamic scenarios.
Highlights
Vehicular ad hoc networks (VANETs) are designed to provide communication between vehicles, as well as between vehicles and infrastructure
We examine a VANET anti-jamming game as in [4,5,6]
We suggest that power included in the vehicle and jammer utility functions is linear, but from the Theorem 1 presented in this paper it follows that the optimal vehicle strategy is to transmit at maximum power; we change the classic formula of the utility function in order to find a non-trivial vehicle strategy
Summary
Vehicular ad hoc networks (VANETs) are designed to provide communication between vehicles, as well as between vehicles and infrastructure. We discuss below several articles that use game theory and machine learning algorithms for finding optimal strategies in the anti-jamming game in various settings. In the multi-channel case, it is assumed that the vehicles change channels according to a predetermined pseudo-random sequence In this situation, we presume that the jammer shares its power between channels because it cannot predict the state of the network in advance. To confirm the simulation results, we formulate and prove theorems that describe the Nash equilibrium of the game, which can be interpreted as the optimal strategy for the vehicle and the jammer. Such a power function is closer to practical implementation, since transmitting on higher power levels requires a greater expenditure of system resources than at low levels Under this assumption, we formulate and prove the Nash equilibrium theorems in both single-channel and multi-channel cases.
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