  The fog radio access network (F-RAN) is a promising paradigm for the fifth
generation wireless communication systems to provide high spectral efficiency
and energy efficiency. Characterizing users to select an appropriate
communication mode among fog access point (F-AP), and device-to-device (D2D) in
F-RANs is critical for performance optimization. Using evolutionary game
theory, we investigate the dynamics of user access mode selection in F-RANs.
Specifically, the competition among groups of potential users space is
formulated as a dynamic evolutionary game, and the evolutionary equilibrium is
the solution to this game. Stochastic geometry tool is used to derive the
proposals' payoff expressions for both F-AP and D2D users by taking into
account the different nodes locations, cache sizes as well as the delay cost.
The analytical results obtained from the game model are evaluated via
simulations, which show that the evolutionary game based access mode selection
algorithm can reach a much higher payoff than the max rate based algorithm.
