In this paper, the problem of semantic information extraction for resour...
Recently, big artificial intelligence (AI) models represented by chatGPT...
This paper investigates the adaptive bitrate (ABR) video semantic
commun...
Over-the-air computation (AirComp) has recently been identified as a
pro...
For vehicular metaverses, one of the ultimate user-centric goals is to
o...
In this paper, we propose a novel complex convolutional neural network (...
Due to the dynamics of wireless environment and limited bandwidth, wirel...
In conventional distributed learning over a network, multiple agents
col...
With the recent developments in engineering quantum systems, the realiza...
To facilitate the deployment of digital twins in Metaverse, the paradigm...
Deep learning (DL)-based channel state information (CSI) feedback method...
Federated learning (FL) refers to a distributed machine learning framewo...
Beamforming with large-scale antenna arrays has been widely used in rece...
This paper studies the exploitation of triple polarization (TP) for
mult...
Real-time intelligence applications in Internet of Things (IoT) environm...
In this paper, the problem of sum-rate maximization for an active
reconf...
The construction of virtual transportation networks requires massive dat...
In this paper, the problem of wireless resource allocation and semantic
...
Semantic communication allows the receiver to know the intention instead...
Unmanned aerial vehicle (UAV) swarms are considered as a promising techn...
Technological advancements have normalized the usage of unmanned aerial
...
Benefited from the advances of deep learning (DL) techniques, deep joint...
This paper investigates the utilization of triple polarization (TP) for
...
Explainable Artificial Intelligence (XAI) is transforming the field of
A...
Federated edge learning (FEL) is a promising paradigm of distributed mac...
In split machine learning (ML), different partitions of a neural network...
In this work, we consider a federated learning model in a wireless syste...
Reconfigurable intelligent surface (RIS) can be employed in a cell-free
...
Cooperative rate splitting (CRS), built upon rate splitting multiple acc...
Communication systems to date primarily aim at reliably communicating bi...
To process and transfer large amounts of data in emerging wireless servi...
This paper investigates the use of the reconfigurable dual-functional su...
In existing computing systems, such as edge computing and cloud computin...
The core requirement of massive Machine-Type Communication (mMTC) is to
...
The main challenge to deploy deep neural network (DNN) over a mobile edg...
With the tremendous advances in the architecture and scale of convolutio...
With the continuous trend of data explosion, delivering packets from dat...
Reconfigurable intelligent surfaces (RISs) have been recently considered...
Reconfigurable intelligent surface (RIS) has emerged as a promising
tech...
In this paper, the problem of minimizing the weighted sum of age of
info...
Federated learning (FL) as a promising edge-learning framework can
effec...
In this paper, the problem of enhancing the quality of virtual reality (...
Wireless communication in the TeraHertz band (0.1–10 THz) is envisioned ...
Traditional machine learning is centralized in the cloud (data centers)....
In this paper, the optimization of deploying unmanned aerial vehicles (U...
Transformer is a type of deep neural network mainly based on self-attent...
Reconfigurable Intelligent Surfaces (RISs) have been recently considered...
In this paper, the problem of unmanned aerial vehicle (UAV) deployment a...
Wireless communication in the TeraHertz band (0.1–10 THz) is envisioned ...
Quantized neural networks with low-bit weights and activations are attra...