FLSTRA: Federated learning in stratosphere
We propose a federated learning (FL) in stratosphere (FLSTRA) system, where a high
altitude platform station (HAPS) facilitates a large number of terrestrial clients to …
altitude platform station (HAPS) facilitates a large number of terrestrial clients to …
Federated learning over LEO satellite
The rapid development of low earth orbit (LEO) satellite communication has driven the
deployment of artificial intelligence (AI) in space, providing various intelligent services like …
deployment of artificial intelligence (AI) in space, providing various intelligent services like …
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 …
COTAF: Convergent over-the-air federated learning
T Sery, N Shlezinger, K Cohen… - GLOBECOM 2020-2020 …, 2020 - ieeexplore.ieee.org
Federated learning (FL) is a framework for distributed learning of centralized models. In FL,
a set of edge devices train a model using their local data, while repeatedly exchanging their …
a set of edge devices train a model using their local data, while repeatedly exchanging their …
Over-the-air federated edge learning with hierarchical clustering
We examine federated learning (FL) with over-the-air (OTA) aggregation, where mobile
users (MUs) aim to reach a consensus on a global model with the help of a parameter server …
users (MUs) aim to reach a consensus on a global model with the help of a parameter server …
Roar-fed: Ris-assisted over-the-air adaptive resource allocation for federated learning
Over-the-air federated learning (OTA-FL) integrates communication and model aggregation
by exploiting the innate superposition property of wireless channels. The approach renders …
by exploiting the innate superposition property of wireless channels. The approach renders …
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 …
Fedsn: A general federated learning framework over leo satellite networks
Recently, a large number of Low Earth Orbit (LEO) satellites have been launched and
deployed successfully in space by commercial companies, such as SpaceX. Due to …
deployed successfully in space by commercial companies, such as SpaceX. Due to …
DFedSat: Communication-Efficient and Robust Decentralized Federated Learning for LEO Satellite Constellations
Low Earth Orbit (LEO) satellites play a crucial role in the development of 6G mobile networks
and space-air-ground integrated systems. Recent advancements in space technology have …
and space-air-ground integrated systems. Recent advancements in space technology have …
IRS Assisted Federated Learning: A Broadband Over-the-Air Aggregation Approach
We consider a broadband over-the-air computation empowered model aggregation
approach for wireless federated learning (FL) systems and propose to leverage an …
approach for wireless federated learning (FL) systems and propose to leverage an …