The growing interest in the Metaverse has generated momentum for members...
With the escalating prevalence of malicious activities exploiting
vulner...
Federated learning (FL) has found many successes in wireless networks;
h...
This article introduces a novel lightweight framework using ambient
back...
Due to its security, transparency, and flexibility in verifying virtual
...
Decoding brain signals can not only reveal Metaverse users' expectations...
This work proposes a novel framework to dynamically and effectively mana...
To enable an intelligent, programmable and multi-vendor radio access net...
With the rising demand for wireless services and increased awareness of ...
Real-time machine learning has recently attracted significant interest d...
Toward user-driven Metaverse applications with fast wireless connectivit...
Federated Learning (FL) with quantization and deliberately added noise o...
In real-world applications, Federated Learning (FL) meets two challenges...
Rate Splitting Multiple Access (RSMA) has emerged as an effective
interf...
Creating and maintaining the Metaverse requires enormous resources that ...
Federated learning (FL) is a new artificial intelligence concept that en...
Rate Splitting Multiple Access (RSMA) has recently emerged as a promisin...
This article aims to study intrusion attacks and then develop a novel
cy...
In Joint Communication and Radar (JCR)-based Autonomous Vehicle (AV) sys...
This paper introduces a novel solution to enable covert communication in...
By executing offloaded tasks from mobile users, edge computing augments
...
Metaverse has recently attracted paramount attention due to its potentia...
Federated Learning (FL) has recently become an effective approach for
cy...
Most conventional Federated Learning (FL) models are using a star networ...
Major bottlenecks of large-scale Federated Learning(FL) networks are the...
This article proposes a cooperative friendly jamming framework for swarm...
Unmanned aerial vehicle (UAV)-assisted data collection has been emerging...
This work aims to jointly optimize the coding and node selection to mini...
This paper develops a novel framework to defeat a super-reactive jammer,...
Unlike theoretical distributed learning (DL), DL over wireless edge netw...
With outstanding features, Machine Learning (ML) has been the backbone o...
In this paper, we propose FedChain, a novel framework for
federated-bloc...
We investigate the performance of multi-user multiple-antenna downlink
s...
Federated learning (FL) can empower Internet-of-Vehicles (IoV) networks ...
Unmanned Aerial Vehicles (UAVs) have been emerging as an effective solut...
Due to the proliferation of smart devices and emerging applications, man...
In this paper, an economic model is proposed for joint time resource
all...
In this paper, we introduce DeepFake, a novel deep reinforcement
learnin...
Mobile service providers (MSPs) are particularly vulnerable to roaming
f...
In intelligent transportation systems (ITS), vehicles are expected to fe...
In this paper, we propose a novel energy-efficient framework for an elec...
In this article, we introduce a novel deception strategy which is inspir...
In this paper, we propose novel approaches using state-of-the-art machin...
We propose a novel multi-tier fog and cloud computing architecture that
...
With conventional anti-jamming solutions like frequency hopping or sprea...
Effective network slicing requires an infrastructure/network provider to...
This letter proposes two novel proactive cooperative caching approaches ...
We propose a two dimension (2D) proactive uplink resource allocation
(2D...
We propose a novel edge computing network architecture that enables edge...
Mobile edge caching/computing has been emerging as a promising paradigm ...