A novel hybrid split and federated learning architecture in wireless UAV networks
The ever-growing use of unmanned aerial vehicles (UAVs) as aerial users is becoming a
major part of the sixth generation (6G) networks, which could provide various applications …
major part of the sixth generation (6G) networks, which could provide various applications …
Federated learning for UAVs-enabled wireless networks: Use cases, challenges, and open problems
The use of Unmanned Aerial Vehicles (UAVs) for wireless networks is rapidly growing as
key enablers of new applications, including: surveillance and monitoring, military, delivery of …
key enablers of new applications, including: surveillance and monitoring, military, delivery of …
Artificial intelligence for enhanced mobility and 5G connectivity in UAV-based critical missions
In the context of Fifth Generation mobile networks (5G), Search and Rescue (SAR) missions
using Unmanned Aerial Vehicles (UAVs) can benefit from a dynamic, intelligent, and …
using Unmanned Aerial Vehicles (UAVs) can benefit from a dynamic, intelligent, and …
Air-to-ground path loss prediction using ray tracing and measurement data jointly driven DNN
With the wide application of unmanned aerial vehicle (UAV), air-to-ground (A2G) channel
characterization is important for efficient and stable UAV-related communications. In this …
characterization is important for efficient and stable UAV-related communications. In this …
Jittering effects analysis and beam training design for UAV millimeter wave communications
W Wang, W Zhang - IEEE Transactions on Wireless …, 2021 - ieeexplore.ieee.org
Jittering effects significantly degrade the performance of UAV millimeter-wave (mmWave)
communications. To investigate the impacts of UAV jitter on mmWave communications, we …
communications. To investigate the impacts of UAV jitter on mmWave communications, we …
Simultaneous navigation and radio mapping for cellular-connected UAV with deep reinforcement learning
Cellular-connected unmanned aerial vehicle (UAV) is a promising technology to unlock the
full potential of UAVs in the future by reusing the cellular base stations (BSs) to enable their …
full potential of UAVs in the future by reusing the cellular base stations (BSs) to enable their …
Machine learning-based hybrid precoding with robust error for UAV mmWave massive MIMO
Unmanned aerial vehicles (UAVs) can now be considered as aerial base stations (BSs) to
support ultra-reliable and low-latency communications by establishing line-of-sight (LoS) …
support ultra-reliable and low-latency communications by establishing line-of-sight (LoS) …
HAPS-UAV-enabled heterogeneous networks: A deep reinforcement learning approach
The integrated use of non-terrestrial network (NTN) entities such as the high-altitude
platform station (HAPS) and low-altitude platform station (LAPS) has become essential …
platform station (HAPS) and low-altitude platform station (LAPS) has become essential …
Decentralized federated learning for UAV networks: Architecture, challenges, and opportunities
Unmanned aerial vehicles (UAVs), or drones, are envisioned to support extensive
applications in next-generation wireless networks in both civil and military fields …
applications in next-generation wireless networks in both civil and military fields …
Distributional reinforcement learning for mmWave communications with intelligent reflectors on a UAV
In this paper, a novel communication framework that uses an unmanned aerial vehicle
(UAV)-carried intelligent reflector (IR) is proposed to enhance multi-user downlink …
(UAV)-carried intelligent reflector (IR) is proposed to enhance multi-user downlink …