Competing Mobile Network Game: Embracing antijamming and jamming strategies with reinforcement learning

Youngjune Gwon, Siamak Dastangoo, Carl Fossa, H. T. Kung
2013 2013 IEEE Conference on Communications and Network Security (CNS)  
We introduce Competing Mobile Network Game (CMNG), a stochastic game played by cognitive radio networks that compete for dominating an open spectrum access. Differentiated from existing approaches, we incorporate both communicator and jamming nodes to form a network for friendly coalition, integrate antijamming and jamming subgames into a stochastic framework, and apply Q-learning techniques to solve for an optimal channel access strategy. We empirically evaluate our Q-learning based strategies
more » ... ng based strategies and find that Minimax-Q learning is more suitable for an aggressive environment than Nash-Q while Friend-or-foe Q-learning can provide the best solution under distributed mobile ad hoc networking scenarios in which the centralized control can hardly be available.
doi:10.1109/cns.2013.6682689 dblp:conf/cns/GwonDFK13 fatcat:7svlvgv2m5eeta5orxeowzordm