Efficient Jamming Resource Allocation Against Frequency-Hopping Spread Spectrum in WSNs with Asynchronous Deep Reinforcement Learning

Jamming against frequency-hopping spread spectrum (FHSS) in wireless sensor networks (WSNs) has been primarily investigated with the follower jamming mode. However, implementing follower jamming in practical applications encounters manifold challenges, such as stringent requirements on hardware perf...

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Veröffentlicht in:	IEEE sensors journal 2024-04, Vol.24 (8), p.1-1
Hauptverfasser:	Rao, Ning, Xu, Hua, Wang, Dan, Qi, Zisen, Zhang, Yue, Gu, Wanyi, Peng, Xiang
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms asynchronous deep reinforcement learning Bandwidths Convergence Decision making Decisions Deep learning Frequency hopping Jamming jamming against FHSS Long Short-Term Memory Markov processes partial-band noise jamming Resource allocation Spectrum allocation Spread spectrum Synchronism Wireless sensor networks
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