Multiple Jammer Attacks on Cognitive Radio Networks over Noisy Channels: A Strategic Game with Incomplete Information

We model the anti-jamming system for cognitive radio networks under multiple jammer attacks using game theory as incomplete information games. The game model has three players: nature (representing channel impairment), jammer, and cognitive radio with sequential moves. Typically, sequential games with incomplete information use the Perfect Bayesian equilibrium solution concept, where beliefs are determined by Bayes' rule to identify the player type. In the proposed Perfect Hidden Markov -Viterbi equilibrium solution concept, beliefs are determined by the Hidden Markov Model - Viterbi decoding instead of Bayes' rule to identify the jammer type. A general form of expression is derived to compute players' payoff for probability-based belief systems to find equilibrium in anti-jamming games with incomplete information under multiple jammer attacks.The simulation results show that over time, with a gradual reduction in the bit error rate at the receiver without any channel coding for Binary Phase Shift Keying (BPSK) modulation and in the noisy Rayleigh fading environment, the proposed Perfect Hidden Markov - Viterbi equilibrium solution concept performs better than Perfect Bayesian equilibriumby 0.8 % and the traditional pseudorandom-based frequency hopping technique by 1 % in terms of the average uncoded bit error rate.