The emergence of delay-sensitive and computationally-intensive mobile applications and services pose a significant challenge for Unmanned Aerial Vehicles (UAVs) devices due to …
MB Driss, E Sabir, H Elbiaze, W Saad - arXiv preprint arXiv:2312.04688, 2023 - arxiv.org
Artificial Intelligence (AI) is expected to play an instrumental role in the next generation of wireless systems, such as sixth-generation (6G) mobile network. However, massive data …
In recent years, the proliferation of unmanned aerial vehicles (UAVs) has increased dramatically. UAVs can accomplish complex or dangerous tasks in a reliable and cost …
The 6th generation mobile network (6G) is expected to be launched in the early 2030s. The architecture of 6G will be the convergence of space, air, ground, and undersea networks …
S Dai, F Meng - Applied Intelligence, 2023 - Springer
Online federated learning (OFL) and online transfer learning (OTL) are two collaborative paradigms for overcoming modern machine learning challenges such as data silos …
This paper considers improving wireless communication and computation efficiency in federated learning (FL) via model quantization. In the proposed bitwidth FL scheme, edge …
Federated learning (FedL) has emerged as a popular technique for distributing model training over a set of wireless devices, via iterative local updates (at devices) and global …
While network coverage maps continue to expand, many devices located in remote areas remain unconnected to terrestrial communication infrastructures, preventing them from …