By integrating recent advances in large language models (LLMs) and gener...
This paper proposes new framework of communication system leveraging
pro...
In this paper, we introduce a novel semantic generative communication (S...
This paper presents a wireless data collection framework that employs an...
Low probability of detection (LPD) has recently emerged as a means to en...
Autoencoder (AE) is a neural network (NN) architecture that is trained t...
Metaverse over wireless networks is an emerging use case of the sixth
ge...
While witnessing the noisy intermediate-scale quantum (NISQ) era and bey...
Recently, vision transformer (ViT) has started to outpace the convention...
Real-time remote control over wireless is an important-yet-challenging
a...
Semantic communication (SC) goes beyond technical communication in which...
Although quantum supremacy is yet to come, there has recently been an
in...
Quantum federated learning (QFL) has recently received increasing attent...
Classical medium access control (MAC) protocols are interpretable, yet t...
This article seeks for a distributed learning solution for the visual
tr...
Traditionally, studies on technical communication (TC) are based on
stoc...
Federated learning (FL) is a key enabler for efficient communication and...
In recent years, quantum computing (QC) has been getting a lot of attent...
This article aims to provide a unified and technical approach to semanti...
In recent years, there have been great advances in the field of decentra...
Mobile devices are indispensable sources of big data. Federated learning...
This paper aims to integrate two synergetic technologies, federated lear...
A mega-constellation of low-altitude earth orbit (LEO) satellites (SATs)...
Spurred by a huge interest in the post-Shannon communication, it has rec...
In this article, we study the problem of air-to-ground ultra-reliable an...
Precise positioning has become one core topic in wireless communications...
In this paper, the problem of robust reconfigurable intelligent surface ...
Wireless channels can be inherently privacy-preserving by distorting the...
The lottery ticket hypothesis (LTH) claims that a deep neural network (i...
Remote state monitoring over wireless is envisaged to play a pivotal rol...
This article studies the joint problem of uplink-downlink scheduling and...
Federated learning (FL) is a promising distributed learning solution tha...
In this book chapter, we study a problem of distributed content caching ...
Knowledge distillation (KD) has enabled remarkable progress in model
com...
Distributed learning frameworks often rely on exchanging model parameter...
Improving the data rate of machine-type communication (MTC) is essential...
A mega-constellation of low-altitude earth orbit (LEO) satellites (SATs)...
This article articulates the emerging paradigm, sitting at the confluenc...
In this paper, we propose a communication-efficiently decentralized mach...
Machine learning (ML) is a promising enabler for the fifth generation (5...
Massive machine-type communication (mMTC) and ultra-reliable and low-lat...
The goal of this work is the accurate prediction of millimeter-wave rece...
Wireless connectivity is instrumental in enabling scalable federated lea...
This letter proposes a novel communication-efficient and privacy-preserv...
User-generated data distributions are often imbalanced across devices an...
A mega-constellation of low-earth orbit (LEO) satellites has the potenti...
Traditional distributed deep reinforcement learning (RL) commonly relies...
Traditional distributed deep reinforcement learning (RL) commonly relies...
The goal of this study is to improve the accuracy of millimeter wave rec...
While Remote control over wireless connections is a key enabler for scal...