Deep learning-aided 6G wireless networks: A comprehensive survey of revolutionary PHY architectures
Deep learning (DL) has proven its unprecedented success in diverse fields such as
computer vision, natural language processing, and speech recognition by its strong …
computer vision, natural language processing, and speech recognition by its strong …
Deep reinforcement learning in the advanced cybersecurity threat detection and protection
The cybersecurity threat landscape has lately become overly complex. Threat actors
leverage weaknesses in the network and endpoint security in a very coordinated manner to …
leverage weaknesses in the network and endpoint security in a very coordinated manner to …
JRNet: Jamming recognition networks for radar compound suppression jamming signals
Q Qu, S Wei, S Liu, J Liang, J Shi - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
As electromagnetic environments in battlefields are more and more complex, there are more
kinds of suppression jamming noise including both single jamming signals and compound …
kinds of suppression jamming noise including both single jamming signals and compound …
Generative AI for secure physical layer communications: A survey
Generative Artificial Intelligence (GAI) stands at the forefront of AI innovation, demonstrating
rapid advancement and unparalleled proficiency in generating diverse content. Beyond …
rapid advancement and unparalleled proficiency in generating diverse content. Beyond …
A comprehensive survey of machine learning applied to radar signal processing
P Lang, X Fu, M Martorella, J Dong, R Qin… - arXiv preprint arXiv …, 2020 - arxiv.org
Modern radar systems have high requirements in terms of accuracy, robustness and real-
time capability when operating on increasingly complex electromagnetic environments …
time capability when operating on increasingly complex electromagnetic environments …
Game theory and reinforcement learning for anti-jamming defense in wireless communications: Current research, challenges, and solutions
L Jia, N Qi, Z Su, F Chu, S Fang… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Due to the inherently open and shared nature of the wireless channels, wireless
communication networks are vulnerable to jamming attacks, and effective anti-jamming …
communication networks are vulnerable to jamming attacks, and effective anti-jamming …
Dynamic spectrum anti-jamming access with fast convergence: A labeled deep reinforcement learning approach
Y Li, Y Xu, G Li, Y Gong, X Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The primary objective of anti-jamming techniques is to ensure that the transmitted data
arrives at the intended receiver without being disturbed or jammed with by any jamming …
arrives at the intended receiver without being disturbed or jammed with by any jamming …
When machine learning meets spectrum sharing security: Methodologies and challenges
The exponential growth of Internet connected systems has generated numerous challenges,
such as spectrum shortage issues, which require efficient spectrum sharing (SS) solutions …
such as spectrum shortage issues, which require efficient spectrum sharing (SS) solutions …
Deep networks for direction of arrival estimation with sparse prior in low SNR
Y Qin - IEEE Access, 2023 - ieeexplore.ieee.org
This work introduces direction of arrival (DOA) estimation considering the sparsity prior in
the low signal to noise ratio (SNR) using deep learning (DL). The sparsity of the …
the low signal to noise ratio (SNR) using deep learning (DL). The sparsity of the …
Jamming recognition based on AC-VAEGAN
Y Tang, Z Zhao, X Ye, S Zheng… - 2020 15th IEEE …, 2020 - ieeexplore.ieee.org
To solve the performance deterioration of jamming recognition method based on deep
learning in the case of small sample set, a jamming recognition method based on AC …
learning in the case of small sample set, a jamming recognition method based on AC …