Distributed learning in wireless networks: Recent progress and future challenges
The next-generation of wireless networks will enable many machine learning (ML) tools and
applications to efficiently analyze various types of data collected by edge devices for …
applications to efficiently analyze various types of data collected by edge devices for …
Evolution of non-terrestrial networks from 5G to 6G: A survey
Non-terrestrial networks (NTNs) traditionally have certain limited applications. However, the
recent technological advancements and manufacturing cost reduction opened up myriad …
recent technological advancements and manufacturing cost reduction opened up myriad …
Edge learning for B5G networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing
To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …
increasingly appealing to exploit distributed data communication and learning. Specifically …
Edge artificial intelligence for 6G: Vision, enabling technologies, and applications
KB Letaief, Y Shi, J Lu, J Lu - IEEE Journal on Selected Areas …, 2021 - ieeexplore.ieee.org
The thriving of artificial intelligence (AI) applications is driving the further evolution of
wireless networks. It has been envisioned that 6G will be transformative and will …
wireless networks. It has been envisioned that 6G will be transformative and will …
Path-planning for unmanned aerial vehicles with environment complexity considerations: A survey
Unmanned aerial vehicles (UAVs) have the potential to make a significant impact in a range
of scenarios where it is too risky or too costly to rely on human labour. Fleets of autonomous …
of scenarios where it is too risky or too costly to rely on human labour. Fleets of autonomous …
Performance optimization for semantic communications: An attention-based reinforcement learning approach
In this paper, a semantic communication framework is proposed for textual data
transmission. In the studied model, a base station (BS) extracts the semantic information …
transmission. In the studied model, a base station (BS) extracts the semantic information …
Federated learning for audio semantic communication
In this paper, the problem of audio semantic communication over wireless networks is
investigated. In the considered model, wireless edge devices transmit large-sized audio …
investigated. In the considered model, wireless edge devices transmit large-sized audio …
Multi-UAV path planning for wireless data harvesting with deep reinforcement learning
Harvesting data from distributed Internet of Things (IoT) devices with multiple autonomous
unmanned aerial vehicles (UAVs) is a challenging problem requiring flexible path planning …
unmanned aerial vehicles (UAVs) is a challenging problem requiring flexible path planning …
Online trajectory and resource optimization for stochastic UAV-enabled MEC systems
The recent development of unmanned aerial vehicle (UAV) and mobile edge computing
(MEC) technologies provides flexible and resilient computation services to mobile users out …
(MEC) technologies provides flexible and resilient computation services to mobile users out …
Overview of distributed machine learning techniques for 6G networks
The main goal of this paper is to survey the influential research of distributed learning
technologies playing a key role in the 6G world. Upcoming 6G technology is expected to …
technologies playing a key role in the 6G world. Upcoming 6G technology is expected to …