A comprehensive survey on 5G-and-beyond networks with UAVs: Applications, emerging technologies, regulatory aspects, research trends and challenges
The rapid advancement of fifth-generation (5G)-and-beyond networks coupled with
unmanned aerial vehicles (UAVs) has opened up exciting possibilities for diverse …
unmanned aerial vehicles (UAVs) has opened up exciting possibilities for diverse …
Delay-optimal task offloading for UAV-enabled edge-cloud computing systems
The emergence of delay-sensitive and computationally-intensive mobile applications and
services pose a significant challenge for Unmanned Aerial Vehicles (UAVs) devices due to …
services pose a significant challenge for Unmanned Aerial Vehicles (UAVs) devices due to …
Federated learning for 6g: Paradigms, taxonomy, recent advances and insights
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 …
wireless systems, such as sixth-generation (6G) mobile network. However, massive data …
[HTML][HTML] Energy-efficient inference on the edge exploiting TinyML capabilities for UAVs
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 …
dramatically. UAVs can accomplish complex or dangerous tasks in a reliable and cost …
FedLEO: An offloading-assisted decentralized federated learning framework for low earth orbit satellite networks
Low Earth orbit (LEO) satellites enable complex Earth observation tasks (eg, remote sensing
and cooperative monitoring) by leveraging large-scale satellite-generated Earth imageries …
and cooperative monitoring) by leveraging large-scale satellite-generated Earth imageries …
Federated learning for green and sustainable 6G IIoT applications
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 …
architecture of 6G will be the convergence of space, air, ground, and undersea networks …
[HTML][HTML] Addressing modern and practical challenges in machine learning: A survey of online federated and transfer learning
Online federated learning (OFL) and online transfer learning (OTL) are two collaborative
paradigms for overcoming modern machine learning challenges such as data silos …
paradigms for overcoming modern machine learning challenges such as data silos …
Performance optimization for variable bitwidth federated learning in wireless networks
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 (FL) via model quantization. In the proposed bitwidth FL scheme, edge …
Parallel successive learning for dynamic distributed model training over heterogeneous wireless networks
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 …
training over a set of wireless devices, via iterative local updates (at devices) and global …
Cooperative federated learning over ground-to-satellite integrated networks: Joint local computation and data offloading
While network coverage maps continue to expand, many devices located in remote areas
remain unconnected to terrestrial communication infrastructures, preventing them from …
remain unconnected to terrestrial communication infrastructures, preventing them from …