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The jamming attack is one of the most severe threats in cognitive radio networks, because it can lead to network degradation and even denial of service. However, a cognitive radio can exploit its ability of dynamic spectrum access and its learning capabilities to avoid jammed channels. In this paper, we study how Q-learning can be used to learn the jammer(More)
We model the power allocation interaction between a cognitive radio and a jammer as a two-player zero-sum game. First, we determine the power allocation strategy for the cognitive radio using a modified version of the Q-learning algorithm against fixed jamming strategies. The learned anti-jamming strategy will be compared to the common waterfilling(More)
The emergence of new wireless services and the growing demand for wireless communications are creating a spectrum shortage problem. Moreover, the current technique of static frequency allocation leads to inefficiency utilization of the available spectrum. Cognitive radio (CR) and dynamic spectrum management (DSM) concepts, aim to solve this imbalance(More)
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