A survey of beam management for mmWave and THz communications towards 6G
Communication in millimeter wave (mmWave) and even terahertz (THz) frequency bands is
ushering in a new era of wireless communications. Beam management, namely initial …
ushering in a new era of wireless communications. Beam management, namely initial …
Supervised contrastive learning for RFF identification with limited samples
Radio-frequency fingerprint (RFF), which comes from the imperfect hardware, is a potential
feature to ensure the security of communication. With the development of deep learning …
feature to ensure the security of communication. With the development of deep learning …
Interpolative metric learning for few-shot specific emitter identification
C Wang, X Fu, Y Wang, G Gui… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Specific emitter identification (SEI) is a potential physical layer authentication technology,
which is one of the most critical complements of upper layer authentication. Radio frequency …
which is one of the most critical complements of upper layer authentication. Radio frequency …
A robust CSI-based Wi-Fi passive sensing method using attention mechanism deep learning
Wi-Fi-based passive sensing is considered as one of the promising sensing techniques in
advanced wireless communication systems due to its wide applications and low deployment …
advanced wireless communication systems due to its wide applications and low deployment …
Failure detector based on vehicle movement prediction in vehicular ad-hoc networks
Vehicular ad hoc network (VANETs) improves road safety and efficiency by organizing
vehicles and infrastructure to provide a platform for application deployment. The availability …
vehicles and infrastructure to provide a platform for application deployment. The availability …
Priority-aware path planning and user scheduling for UAV-mounted MEC networks: A deep reinforcement learning approach
X Zheng, Y Wu, L Zhang, M Tang, F Zhu - Physical Communication, 2024 - Elsevier
Owing to the flexibility and controllability, unmanned aerial vehicle (UAV) is frequently
integrated into mobile edge computing (MEC) network to improve the system performance …
integrated into mobile edge computing (MEC) network to improve the system performance …
Enhanced Specific Emitter Identification With Limited Data Through Dual Implicit Regularization
Y Peng, X Zhang, L Guo, C Ben, Y Liu… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
Specific Emitter Identification (SEI) is a critical technology for physical layer authentication in
wireless communications and the Internet of Things. Leveraging the inherent and hard-to …
wireless communications and the Internet of Things. Leveraging the inherent and hard-to …
Unsupervised Power Allocation Based on Combination of Edge Aggregated Graph Attention Network with Deep Unfolded WMMSE
To address the challenge of optimizing power distribution for transmitter-receiver pairs within
ad hoc wireless networks, deep learning techniques have been employed to navigate the …
ad hoc wireless networks, deep learning techniques have been employed to navigate the …
Class-Incremental Learning for Recognition of Complex-Valued Signals
Signal recognition, essential in both military and civilian applications, often deals with an
expanding array of signal classes due to the emergence of new communication devices …
expanding array of signal classes due to the emergence of new communication devices …
TBP: Temporal Beam Prediction for Mobile Millimeter-Wave Networks
Beam selection is a fundamental problem in millimeter wave (mmWave) communication
systems. Yet, most existing beam selection techniques focus on the exploitation of spatial …
systems. Yet, most existing beam selection techniques focus on the exploitation of spatial …