Empowering edge intelligence by air-ground integrated federated learning
… First, we introduce air-to-air (A2A) FL, where the training process happens within the aerial
networks only. One typical example is the FL framework proposed in [4], which enables FL …
networks only. One typical example is the FL framework proposed in [4], which enables FL …
Privacy-preserving federated learning for UAV-enabled networks: Learning-based joint scheduling and resource management
… federated learning (AFL) to achieve fast convergence speed and high learning accuracy
for multiUAV-enabled wireless networks. The … network consists of N UAVs and K single-antenna …
for multiUAV-enabled wireless networks. The … network consists of N UAVs and K single-antenna …
Exploiting UAV for air–ground integrated federated learning: A joint UAV location and resource optimization approach
Y Jing, Y Qu, C Dong, W Ren, Y Shen… - … and Networking, 2023 - ieeexplore.ieee.org
… radio access network for wireless federated learning acceler… based collaborative content
caching towards 6g networks,” … -aerial-space networks: An asynchronous federated learning …
caching towards 6g networks,” … -aerial-space networks: An asynchronous federated learning …
Federated learning for task and resource allocation in wireless high-altitude balloon networks
… Since a directional antenna is adopted at each HAB, the connectivity between a given
HAB and a given user can be available for data transmission only if the directional antenna is …
HAB and a given user can be available for data transmission only if the directional antenna is …
UAV communications for sustainable federated learning
… data privacy in conventional deep learning, the concept of federated learning (FL) has
been … We consider a network setup with a rotary-wing single-antenna UAV and K single-antenna …
been … We consider a network setup with a rotary-wing single-antenna UAV and K single-antenna …
Federated learning in the sky: Aerial-ground air quality sensing framework with UAV swarms
… To this end, this article proposes a new federated learning (FL)-based aerial-ground air …
-to-end learning from haze features of haze images taken by unmanned aerial vehicles (UAVs) …
-to-end learning from haze features of haze images taken by unmanned aerial vehicles (UAVs) …
Energy-efficient federated learning over UAV-enabled wireless powered communications
… UAV is data collection from network sites [18]. … network sites and then use the collected
data for network upgrading purposes. The application of aerial access networks for FL networks …
data for network upgrading purposes. The application of aerial access networks for FL networks …
A lightweight federated learning based privacy preserving B5G pandemic response network using unmanned aerial vehicles: A proof-of-concept
… response network using a proof-of-concept, aerial–terrestrial network … aerial vehicles (UAVs),
a lightweight federated learning model is proposed to collaboratively yet privately learn …
a lightweight federated learning model is proposed to collaboratively yet privately learn …
Olive branch learning: A topology-aware federated learning framework for space-air-ground integrated network
… [18] propose an FL-based air quality sensing framework in the aerial-ground integrated
network, where unmanned aerial vehicles (UAVs) collaboratively monitor the air quality index (…
network, where unmanned aerial vehicles (UAVs) collaboratively monitor the air quality index (…
Toward energy-efficient distributed federated learning for 6G networks
… to the aerial base … aerial base station. The idea behind DBFL is that if the local clients are
not able to directly connect to the aerial base station, they can still perform federated learning …
not able to directly connect to the aerial base station, they can still perform federated learning …