Jamming-resilient algorithm for underwater cognitive acoustic networks
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 c...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-08-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147717726309 |
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| Summary: | 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. |
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| ISSN: | 1550-1477 |