Radio frequency anti-jamming capability improvement for cognitive radio networks: An evolutionary game theoretical approach

Abstract

A cognitive radio is a smart radio that can be programmed and adjusted dynamically on the fly to suit the contextual environmental needs. Many anti-jamming schemes available to protect the Cognitive Radio Networks from jamming attack uses frequency hopping techniques which are deterministic in nature. The deterministic frequency hopping technique is vulnerable to attack at some stage in the real-world scenario. The proposed anti-jamming system for cognitive radio network with adaptive frequency hopping technique efficiently thwarts the RF jamming attack. In the presences of a reactive jammer, two techniques are used to achieve the adaptive frequency hopping: (i) when channel availability reduces below 75 % the Hidden Markov Model (HMM) based algorithm is used, (ii) when the system is in critical state (i.e. channel availability reduces further below 25 %) the interaction between Cognitive radio node and the jammer is modelled using Evolutionary Game Theory (EGT). The results obtained from both models are improved further to find most suitable channel. The simulation results show that the anti-jamming system significantly decreases the probability of bit error to about 48% in the presences of reactive jammer.