Learning-Based Multi-Domain Anti-Jamming Communication with Unknown Information [PDF]
Electronics, 2023 Due to the open nature of the wireless channel, wireless networks are vulnerable to jamming attacks. In this paper, we try to solve the anti-jamming problem caused by smart jammers, which can adaptively adjust the jamming channel and the jamming power ...
Yongcheng Li, Jinchi Wang, Zhenzhen Gao
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Multi-regional Anti-jamming Communication Scheme Based on Transfer Learning and Q Learning [PDF]
KSII Transactions on Internet and Information Systems, 2019 The smart jammer launches jamming attacks which degrade the transmission reliability. In this paper, smart jamming attacks based on the communication probability over different channels is considered, and an anti-jamming Q learning algorithm (AQLA) is ...
Chen Han, Yingtao Niu
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A Capacity Enhancement Method for Frequency-Hopping Anti-Jamming Communication Systems [PDF]
Electronics, 2023 In this paper, we study the enhancement of channel transmission information by expanding the transmission channel in the frequency-hopping rate dimension in a communication system.
Ze Yu, Zhisong Hao, Wang Yao, Min Jia
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Compromise-resilient anti-jamming communication in wireless sensor networks [PDF]
Wireless Networks, 2011 Jamming is a kind of Denial-of-Service attack in which an adversary purposefully emits radio frequency signals to corrupt the wireless transmissions among normal nodes. Although some research has been conducted on countering jamming attacks, few works consider jamming attacks launched by insiders, where an attacker first compromises some legitimate ...
Xuan Jiang +3 more
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Schemes for Anti-Jamming Broadcast Communication: Research Report
, 2011 Der-Yeuan Yu
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Survey on cognitive anti‐jamming communications [PDF]
IET Communications, 2020 In this study, the authors review various jamming and anti‐jamming strategies in the context of cognitive radios (CRs). The study explores different jamming models and classifies them according to their functionality. Furthermore, a study of jamming detection techniques is provided to enable a CR to identify different jamming signals.
Mohamed A. Aref +2 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Methods based on convolutional neural networks (CNNs) have become a vital offshoot for hyperspectral image (HSI) classification. In recent years, the 3-D CNN (3-DCNN) has become dominant due to its excellent capability of extracting features.
Yaxiu Sun +4 more
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An Improved Anti-Jamming Method Based on Deep Reinforcement Learning and Feature Engineering
IEEE Access, 2022 To improve the performance of anti-jamming communication in dynamic and adversarial jamming environment, an improved anti-jamming method is proposed based on deep reinforcement learning and feature engineering.
Xin Chang +4 more
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Pattern-Aware Intelligent Anti-Jamming Communication: A Sequential Deep Reinforcement Learning Approach [PDF]
IEEE Access, 2019 This paper investigates the problem of anti-jamming communication in dynamic and intelligent jamming environment. A sequential deep reinforcement learning algorithm (SDRLA) without prior information is proposed, and raw spectrum information is used as ...
Songyi Liu +7 more
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Achieving Hiding and Smart Anti-Jamming Communication: A Parallel DRL Approach against Moving Reactive Jammer [PDF]
IEEE Transactions on CommunicationsThis paper addresses the challenge of anti-jamming in moving reactive jamming scenarios. The moving reactive jammer initiates high-power tracking jamming upon detecting any transmission activity, and when unable to detect a signal, resorts to ...
Yangyang Li +7 more
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