Diffusion models (DM) can gradually learn to remove noise, which have be...
Fast and precise beam alignment is crucial for high-quality data transmi...
Degraded broadcast channels (DBC) are a typical multi-user communication...
Diffusion models (DM) can gradually learn to remove noise, which have be...
Vertical federated learning (FL) is a collaborative machine learning
fra...
This paper investigates the problem of activity detection and channel
es...
Extremely large-scale array (XL-array) communications can significantly
...
In this paper, we consider a cooperative communication network where mul...
Coded distributed computing can alleviate the communication load by
leve...
As a prospective key technology for the next-generation wireless
communi...
This paper studies the temporally-correlated massive access system where...
This paper investigates the effective capacity of a point-to-point
ultra...
Semantic communication is implemented based on shared background knowled...
As an edge intelligence algorithm for multi-device collaborative trainin...
In learning-based semantic communications, neural networks have replaced...
One of the main focuses in distributed learning is communication efficie...
Reconfigurable intelligent surface (RIS) has attracted extensive attenti...
Integrated ultra-massive multiple-input multiple-output (UM-MIMO) and
in...
This letter considers temporal-correlated massive access, where each dev...
Existing deep learning-enabled semantic communication systems often rely...
Reconfigurable intelligent surfaces (RISs) have emerged as a prospective...
This paper considers a reconfigurable intelligent surface (RIS)-aided
mi...
Reconfigurable intelligent surfaces (RISs) are able to provide passive
b...
This paper considers a reconfigurable intelligent surface (RIS)-aided
mi...
One of the main focus in federated learning (FL) is the communication
ef...
This paper considers the massive connectivity problem in an asynchronous...
A multi-cell mobile edge computing network is studied, in which each use...
To enable communication-efficient federated learning, fast model aggrega...
Edge caching and computing have been regarded as an efficient approach t...
This work investigates the degrees of freedom (DoF) of a downlink cache-...
This paper investigates learning-based caching in small-cell networks (S...
This paper studies the computation-communication tradeoff in a heterogen...
In traditional cache-enabled small-cell networks (SCNs), a user can suff...
Today's mobile data traffic is dominated by content-oriented traffic. Ca...
Existing works on task offloading in mobile edge computing (MEC) network...
In this paper, we present a novel mobile edge computing (MEC) model wher...
Full-duplex self-backhauling is promising to provide cost-effective and
...
Mobile-edge computing (MEC) has recently emerged as a cost-effective par...
Computation task service delivery in a computing-enabled and caching-aid...
This study focuses on edge computing in dense millimeter wave
vehicle-to...
Coded caching can create coded multicasting thus significantly accelerat...
In this paper, we study the coexistence and synergy between edge and cen...
Virtual reality (VR) over wireless is emerging as an important use case ...
This paper has the following ambitious goal: to convince the reader that...
This paper aims to characterize the synergy of distributed caching and
w...
Mobile virtual reality (VR) delivery is gaining increasing attention fro...
Proactive caching is an effective way to alleviate peak-hour traffic
con...
Caching in multi-cell networks faces a well-known dilemma, i.e., to cach...
The demand for providing multicast services in cellular networks is
cont...
For most wireless services with variable rate transmission, both average...