For the 6G mobile networks, in-situ model downloading has emerged as an
...
5G has expanded the traditional focus of wireless systems to embrace two...
With the proliferation of distributed edge computing resources, the 6G m...
With the advent of emerging IoT applications such as autonomous driving,...
Federated Learning (FL) is a widely embraced paradigm for distilling
art...
The increasingly deeper neural networks hinder the democratization of
pr...
Distributed tensor decomposition (DTD) is a fundamental data-analytics
t...
Sensing is envisioned as a key network function of the 6G mobile network...
As a new function of 6G networks, edge intelligence refers to the ubiqui...
Although considerable progress has been obtained in neural network
quant...
To facilitate the development of Internet of Things (IoT) services,
trem...
Departing from the classic paradigm of data-centric designs, the 6G netw...
The sixth-generation (6G) mobile networks are expected to feature the
ub...
Mobile edge computing (MEC) is a promising technology for enhancing the
...
Distributed optimization concerns the optimization of a common function ...
The deployment of inference services at the network edge, called edge
in...
To support the unprecedented growth of the Internet of Things (IoT)
appl...
In edge inference, an edge server provides remote-inference services to ...
A fundamental algorithm for data analytics at the edge of wireless netwo...
In 1940s, Claude Shannon developed the information theory focusing on
qu...
Federated learning (FL) is a popular framework for training an AI model ...
The rapid development of artificial intelligence together with the power...
With the advent of 5G technology, the notion of latency got a prominent ...
The next-generation of wireless networks will enable many machine learni...
In this paper, we propose a novel wireless architecture, mounted on a
hi...
The deployment of federated learning in a wireless network, called feder...
Federated edge learning (FEEL) is a widely adopted framework for trainin...
The ever-growing popularity and rapid improving of artificial intelligen...
Mobile-edge computing (MEC) enhances the capacities and features of mobi...
Wireless power transfer (WPT) is an emerging paradigm that will enable u...
The ever-growing popularity and rapid improving of artificial intelligen...
A main edge learning paradigm, called partitioned edge learning (PARTEL)...
Wireless data aggregation (WDA), referring to aggregating data distribut...
Multi-point vehicular positioning is one essential operation for autonom...
Wireless connectivity creates a computing paradigm that merges communica...
This paper considers a multi-cell AirComp network and investigates the
o...
Edge machine learning involves the deployment of learning algorithms at ...
In this paper, we investigate the scheduling design of a mobile edge
com...
In cellular federated edge learning (FEEL), multiple edge devices holdin...
To leverage data and computation capabilities of mobile devices, machine...
Federated edge learning (FEEL) is a popular framework for model training...
The next-generation wireless networks are envisioned to support large-sc...
The massive sensing data generated by Internet-of-Things will provide fu...
In the near future, Internet-of-Things (IoT) is expected to connect bill...
The 5G network connecting billions of IoT devices will make it possible ...
Edge machine learning involves the deployment of learning algorithms at ...
With the prevalence of intelligent mobile applications, edge learning is...
Vehicle-to-Everything (V2X) will create many new opportunities in the ar...
Edge machine learning involves the development of learning algorithms at...
In this paper, we study the power control problem for Over-the-air
compu...