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Jamming Bandits—A Novel Learning Method for Optimal Jamming
2016
IEEE Transactions on Wireless Communications
Can an intelligent jammer learn and adapt to unknown environments in an electronic warfare-type scenario? In this paper, we answer this question in the positive, by developing a cognitive jammer that adaptively and optimally disrupts the communication between a victim transmitter-receiver pair. We formalize the problem using a multiarmed bandit framework where the jammer can choose various physical layer parameters such as the signaling scheme, power level and the on-off/pulsing duration in an
doi:10.1109/twc.2015.2510643
fatcat:bepamrvjgbff3kd6373ac3nuzq