Abstract

This study considers jamming and anti-jamming in interference channels by way of smart hopping; and differs from the existing research studies that focus on random hopping in dedicated channels. This study additionally differs from the existing works by way of utilising inference and logical reasoning by both the jammer and target-transmitter to predict the opponent's strategy and choose the most effective counter strategy. The jammer uses a novel strategy to degrade the target-user's signal-to-interference-plus-noise-ratio by directly jamming the target-transmitter's channel, and forcing other transmitters to shift to the target-transmitter's channel. Two scenarios are considered for a target transmitter to response: a high transmit-power target-user utilises smart channel-hopping to force low transmit-power users to concurrently use a channel not hopped by the target-user to confuse the jammer, and a low transmit-power target-user evades the jammer by channel-hopping. The authors propose two-controller and single-controller stochastic games for the first and latter scenarios, respectively, to model interactions with the jammer; and propose a Q-learning algorithm to obtain smart channel hopping sequences for both the jammer and the target-transmitter. Simulations show that the proposed anti-jamming scheme outperforms alternative strategies, including random channel-hopping and transmit-power control in reducing the probability of successful jamming.

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