Federated learning for intelligent transmission with space-air-ground integrated network (SAGIN) toward 6G
The future intelligent devices requires ultra-low communication delay and high QoS
requirement for the following beyond-5G network. Space-air-ground Integrated Network …
requirement for the following beyond-5G network. Space-air-ground Integrated Network …
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… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recently, many exciting usage scenarios and groundbreaking technologies for sixth
generation (6G) networks have drawn more and more attention. The revolution of 6G mainly …
generation (6G) networks have drawn more and more attention. The revolution of 6G mainly …
Optimization Design for Federated Learning in Heterogeneous 6G Networks
With the rapid advancement of 5G networks, billions of smart Internet of Things (IoT) devices
along with an enormous amount of data are generated at the network edge. While still at an …
along with an enormous amount of data are generated at the network edge. While still at an …
Deep reinforcement learning assisted client selection in non-orthogonal multiple access based federated learning
To reap the benefit of big data generated by the massive number of Internet of Things (IoT)
devices while preserving data privacy, federated learning (FL) has been proposed to enable …
devices while preserving data privacy, federated learning (FL) has been proposed to enable …
Distributed deep reinforcement learning assisted resource allocation algorithm for space-air-ground integrated networks
To realize the Interconnection of Everything (IoE) in the 6G vision, the space-based, air-
based, and ground-based networks have shown a trend of integration. Compared with the …
based, and ground-based networks have shown a trend of integration. Compared with the …
Joint device scheduling and bandwidth allocation for federated learning over wireless networks
Federated Learning (FL) has been widely used to train shared machine learning models
while addressing the privacy concerns. When deployed in wireless networks, bandwidth …
while addressing the privacy concerns. When deployed in wireless networks, bandwidth …
Federated imitation learning: A cross-domain knowledge sharing framework for traffic scheduling in 6G ubiquitous IoT
The ubiquitous Internet of Things (IoT) system is a key component of future 6G networks to
realize a fully connected world. Extensive efforts have been made to provide on-demand …
realize a fully connected world. Extensive efforts have been made to provide on-demand …
Federated-learning-based client scheduling for low-latency wireless communications
Motivated by the ever-increasing demands for massive data processing and intelligent data
analysis at the network edge, federated learning (FL), a distributed architecture for machine …
analysis at the network edge, federated learning (FL), a distributed architecture for machine …
DetFed: Dynamic resource scheduling for deterministic federated learning over time-sensitive networks
In this paper, we present a three-layer (ie, device, field, and factory layers) deterministic
federated learning (FL) framework, named DetFed, which accelerates collaborative learning …
federated learning (FL) framework, named DetFed, which accelerates collaborative learning …
Device scheduling with fast convergence for wireless federated learning
Owing to the increasing need for massive data analysis and model training at the network
edge, as well as the rising concerns about the data privacy, a new distributed training …
edge, as well as the rising concerns about the data privacy, a new distributed training …
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