Vehicles in platoons need to process many tasks to support various real-...
Low-latency communication plays an increasingly important role in
delay-...
The flexible-position multiple-input multiple-output (MIMO), such as flu...
Extremely large-scale multiple-input-multiple-output (XL-MIMO), which of...
Federated Learning (FL) is a promising distributed learning mechanism wh...
Holographic MIMO communication was proposed to sufficiently exploit the
...
Driven by the interplay among artificial intelligence, digital twin, and...
Federated learning (FL) has prevailed as an efficient and privacy-preser...
Cell-free (CF) massive multiple-input multiple-output (MIMO) systems, wh...
Terahertz ultra-massive MIMO (THz UM-MIMO) is envisioned as one of the k...
In frequency-division duplexing (FDD) massive multiple-input multiple-ou...
Reliability is of paramount importance for the physical layer of wireles...
The rapid advancement of artificial intelligence technologies has given ...
As a promising integrated computation and communication learning paradig...
In limited feedback multi-user multiple-input multiple-output (MU-MIMO)
...
With the development of innovative applications that demand accurate
env...
Efficient multiple-input multiple-output (MIMO) detection algorithms wit...
Terahertz ultra-massive multiple-input multiple-output (THz UM-MIMO) is
...
Existing deep learning-enabled semantic communication systems often rely...
This paper focuses on the ultimate limit theory of image compression. It...
Deep learning-based approaches have been developed to solve challenging
...
Federated learning (FL) is a promising paradigm to enable privacy-preser...
The development of emerging applications, such as autonomous transportat...
Integrated sensing and communication enables sensing capability for wire...
Federated learning (FL) has recently emerged as a transformative paradig...
Cell-free massive MIMO is one of the core technologies for future wirele...
The thriving of artificial intelligence (AI) applications is driving the...
Queue length violation probability, i.e., the tail distribution of the q...
The emerging Industrial Internet of Things (IIoT) is driving an ever
inc...
In recent years, there has been a surge in applying deep learning to var...
The recently commercialized fifth-generation (5G) wireless communication...
The conventional design of wireless communication systems typically reli...
Graph convolutional networks (GCNs) have recently enabled a popular clas...
In cell-free massive MIMO networks, an efficient distributed detection
a...
Channel estimation and beamforming play critical roles in frequency-divi...
Resource management plays a pivotal role in wireless networks, which,
un...
Over-the-air computation (AirComp) is a disruptive technique for fast
wi...
Federated learning (FL) has recently emerged as an important and promisi...
Federated learning (FL) is a promising and powerful approach for trainin...
Intelligent reflecting surface (IRS) is a promising enabler for
next-gen...
In this paper, we investigate the decentralized statistical inference
pr...
Federated learning is a collaborative machine learning framework to trai...
As an emerging technique, mobile edge computing (MEC) introduces a new
p...
Antenna selection is capable of reducing the hardware complexity of mass...
Intelligent reflecting surfaces (IRSs) are revolutionary enablers for
ne...
Deep learning has recently emerged as a disruptive technology to solve
c...
There are numerous scenarios in source coding where not only the code le...
Mobile edge computing (MEC) has been considered as a promising technique...
Massive MIMO has been regarded as a key enabling technique for 5G and be...
We consider an Internet of Things (IoT) system in which a sensor observe...