Communication networks are important infrastructures in contemporary society. There are
still many challenges that are not fully solved and new solutions are proposed continuously …

The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …

Deep learning has recently emerged as a disruptive technology to solve challenging radio
resource management problems in wireless networks. However, the neural network …

Intelligent reflecting surface (IRS), which consists of a large number of tunable reflective
elements, is capable of enhancing the wireless propagation environment in a cellular …

It has been a long-held belief that judicious resource allocation is critical to mitigating
interference, improving network efficiency, and ultimately optimizing wireless communication …

We consider the problem of optimally allocating resources across a set of transmitters and
receivers in a wireless network. The resulting optimization problem takes the form of …

Optimization theory assisted algorithms have received great attention for precoding design
in multiuser multiple-input multiple-output (MU-MIMO) systems. Although the resultant …

In recent years, with the rapid enhancement of computing power, deep learning methods
have been widely applied in wireless networks and achieved impressive performance. To …

Deep learning-based approaches have been developed to solve challenging problems in
wireless communications, leading to promising results. Early attempts adopted neural …

A well-trained deep neural network (DNN) enables real-time resource allocation by learning
the relationship between a policy and its impacting parameters. When wireless systems …