Abstract
Due to the limit spectrum resource in the underwater acoustic networks, underwater cognitive acoustic communication is a promising technique. The channel sharing mechanism in cognitive networks can improve the communication capacity efficiently. Jamming attack is a common deny of service attack in cognitive networks. In the underwater cognitive acoustic networks, the anti-jamming problem is quite different from cognitive radio networks. It calls for an effective anti-jamming strategy in the cognitive acoustic channel access. In this article, we propose an online learning anti-jamming algorithm called multi-armed bandit–based acoustic channel access algorithm to achieve the jamming-resilient cognitive acoustic communication. The imperfect channel sensing and the constraints of underwater acoustic communication are considered in the anti-jamming game. Under different kinds of jamming attacks, the channel utilization can be improved with our jamming-resilient approach.
Original language | English |
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Pages (from-to) | 1-14 |
Number of pages | 14 |
Journal | International Journal of Distributed Sensor Networks |
Volume | 13 |
Issue number | 8 |
DOIs | |
State | Published - 1 Aug 2017 |
Keywords
- anti-jamming
- channel access
- hidden Markov model
- multi-armed bandit
- Underwater cognitive acoustic network