Joint source and channel coding (JSCC) has attracted increasing attentio...
Current privacy-aware joint source-channel coding (JSCC) works aim at
av...
Due to the dynamics of wireless environment and limited bandwidth, wirel...
In this paper, the problem of joint communication and sensing is studied...
In this paper, the performance optimization of federated learning (FL), ...
In this paper, the problem of wireless resource allocation and semantic
...
Semantic communication allows the receiver to know the intention instead...
In this paper, a semantic communication framework for image transmission...
In this paper, a novel paradigm of mobile edge-quantum computing (MEQC) ...
Pushing artificial intelligence (AI) from central cloud to network edge ...
This paper considers improving wireless communication and computation
ef...
In this work, we consider a federated learning model in a wireless syste...
In this paper, a semantic communication framework is proposed for textua...
In this paper, a new communication-efficient federated learning (FL)
fra...
Recent studies show that depression can be partially reflected from huma...
Cellular networks, such as 5G systems, are becoming increasingly complex...
Model-based reinforcement learning is a widely accepted solution for sol...
In this paper, the deployment of federated learning (FL) is investigated...
The next-generation of wireless networks will enable many machine learni...
In this paper, the problem of minimizing the weighted sum of age of
info...
In this paper, a lifelong learning problem is studied for an Internet of...
Limited radio frequency (RF) resources restrict the number of users that...
The recent development of deep learning methods provides a new approach ...
A new federated learning (FL) framework enabled by large-scale wireless
...
In this paper, the problem of enhancing the quality of virtual reality (...
The fifth-generation (5G) of cellular networks use revolutionary and
evo...
Traditional machine learning is centralized in the cloud (data centers)....
In this paper, the optimization of deploying unmanned aerial vehicles (U...
In this paper, the problem of the trajectory design for a group of
energ...
In this paper, the problem of unmanned aerial vehicle (UAV) deployment a...
In this paper, a joint task, spectrum, and transmit power allocation pro...
In this paper, the problem of delay minimization for federated learning ...
Traditional deep learning models are trained at a centralized server usi...
Internet of Things (IoT) services will use machine learning tools to
eff...
In this paper, the design of an optimal trajectory for an energy-constra...
This paper investigates the problem of resource allocation for a wireles...
In this paper, the problem of minimizing energy and time consumption for...
In this paper, a machine learning based deployment framework of unmanned...
Unmanned aerial vehicle (UAV) swarms must exploit machine learning (ML) ...
Artificial intelligence (AI) assisted unmanned aerial vehicle (UAV) aide...
In this paper, the convergence time of federated learning (FL), when dep...
In this paper, the problem of energy efficient transmission and computat...
In this paper, the problem of training federated learning (FL) algorithm...
In this paper, the problem of optimizing the deployment of unmanned aeri...
In this paper, the problem of user association and resource allocation i...
In this paper, the echo state network (ESN) memory capacity, which repre...
In this paper, the problem of maximizing the wireless users' sum-rate fo...
A novel approach that combines visible light communication (VLC) with
un...
The ongoing deployment of 5G cellular systems is continuously exposing t...
In this paper, the problem of trajectory design of unmanned aerial vehic...