Convolutional neural networks (CNNs) have received widespread attention due to their
powerful modeling capabilities and have been successfully applied in natural language …

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

Along with the rapid developments in communication technologies and the surge in the use
of mobile devices, a brand-new computation paradigm, edge computing, is surging in …

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

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 …

We study the problem of optimal power allocation in a single-hop ad hoc wireless network.
In solving this problem, we depart from classical purely model-based approaches and …

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 …

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 …

The Internet of Things (IoT) allows physical devices to be connected over the wireless
networks. Although device-to-device (D2D) communication has emerged as a promising …