Fast Adaptive Jamming Resource Allocation Against Frequency-Hopping Spread Spectrum in Wireless Sensor Networks via Meta-Deep-Reinforcement-Learning

Partial-band noise jamming is an important countermeasure against frequency-hopping spread spectrum technology in wireless sensor networks, and the jamming resource allocation (JRA) problem involved is a high-dimensional combinatorial optimization and also an NP-hard problem. Moreover, the users can...

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Veröffentlicht in:	IEEE transactions on aerospace and electronic systems 2024-12, Vol.60 (6), p.7676-7693
Hauptverfasser:	Rao, Ning, Xu, Hua, Qi, Zisen, Wang, Dan, Zhang, Yue
Format:	Artikel
Sprache:	eng
Schlagworte:	Aerospace and electronic systems Combinatorial analysis Decision making Deep learning Deep reinforcement learning Frequency hopping Jamming jamming against frequency-hopping spread spectrum (FHSS) meta-learning Neural networks Optimization Resource allocation Resource management Spread spectrum Task analysis Wireless sensor networks wireless sensor networks (WSNs)
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