Resource management plays a pivotal role in wireless networks, which, unfortunately, leads
to challenging NP-hard problems. Artificial Intelligence (AI), especially deep learning …

Machine learning has become successful in solving wireless interference management
problems. Different kinds of deep neural networks (DNNs) have been trained to accomplish …

Deep neural networks have recently emerged as a disruptive technology to solve NP-hard
wireless resource allocation problems in a real-time manner. However, the adopted neural …

We consider the problems of user selection and power control in wireless interference
networks, comprising multiple access points (APs) communicating with a group of user …

With the great success of deep learning (DL) in image classification, speech recognition,
and other fields, more and more studies have applied various neural networks (NNs) to …

As the next generation of mobile systems evolves, artificial intelligence (AI) is expected to
deeply integrate with wireless communications for resource management in variable …

Over the last decade the deployment paradigm of the mobile networks has shifted from
complex hierarchical structures towards decoupling of the control and transmission planes …

In order to achieve high data rate and ubiquitous connectivity in future wireless networks, a
key task is to efficiently manage the radio resource by judicious beamforming and power …

Next-generation wireless networks (NGWN) have a substantial potential in terms of
supporting a broad range of complex compelling applications both in military and civilian …

Connection management is an important problem for any wireless network to ensure smooth
and well-balanced operation throughout. Traditional methods for connection management …