Abstract Internet of Things (IoT) generates unlimited data, which should be collected and forwarded toward a central controller (CC) for further processing and decision-making …
P Zhang, N Chen, S Shen, S Yu, N Kumar… - IEEE Network, 2023 - ieeexplore.ieee.org
AI-enabled Beyond 5G (B5G) and 6G technologies are promising candidates to support the future generation Space-Air-Ground Integrated Networks (SAGINs). The highly dynamic …
W Jiang, H Han, Y Zhang, J Mu - Information Fusion, 2024 - Elsevier
Satellite–terrestrial integrated networks (STINs) have been proposed for B5G/6G mobile communication, and the increase in the computation and communication capacities of …
Since the base station-centric wireless coverage mode of 5G is difficult to support future stereoscopic global wireless coverage demands, the future infrastructure of 6G satellite …
Federated learning (FL) has recently emerged as a distributed machine learning paradigm for systems with limited and intermittent connectivity. This paper presents the new context …
P Yue, J An, J Zhang, G Pan, S Wang, P Xiao… - Authorea …, 2023 - techrxiv.org
On the Security of LEO Satellite Communication Systems: Vulnerabilities, Countermeasures, and Future Trends Page 1 P osted on 11 Jan 2020 — CC-BY-NC-SA 4 — h ttps://doi.org/10.36227/techrx …
T Zhang, KY Lam, J Zhao, J Feng - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Federated Learning (FL) has been widely used to train shared machine learning models while addressing the privacy concerns. When deployed in wireless networks, bandwidth …
Federated Learning (FL) is an emerging Artificial Intelligence (AI) paradigm enabling multiple parties to train a model collaboratively without sharing their data. With the upcoming …
X Chen, J Tan, L Kang, F Tang… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Frequency selective surfaces (FSSs) have attracted extensive attention for suppressing interference and improving channel quality and coverage by selectively transmitting or …