jamming
Given the non-cooperative relationship between the transmitter and the jammer, two main challenges are addressed in this paper: how to model their interactions and how to devise a jamming strategy without prior knowledge of the transmitter. A non-zero-sum game is used to model and analyze such non-cooperative interactions. An approximate mixed-strategy Nash equilibrium (NE) under complete information is derived to serve as a benchmark for comparison.
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This data set provides complex-baseband samples of vehicle-to-vehicle communication (V2V) radios in the presence of primitive jamming signals. Up to 600 vehicles are simulated in this dataset using commerical IEEE 802.11p radios. Supporting example code found on CodeOcean can be used for developing novel physical layer based jamming detection and mitigation strategies using machine learning for ad hoc vehicular networks.
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Future wireless networks must incorporate awareness, adaptability, and intelligence as fundamental building elements in order to meet the wide range of requirements of the next-generation communication systems. Wireless sensing techniques can be used to gather awareness from the radio signals present in the surroundings. However, threats from hostile attackers, such as jamming, eavesdropping, and manipulation, are also present along with this. This paper describes in detail an RF-jamming detection test-bed and provides experimentally measured data.
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