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 …

Deep neural networks (DNNs) have shown great success in completing complex tasks.
However, DNNs inevitably bring high computational cost and storage consumption due to …

Millimeter-wave (mmWave) communication has been regarded as one of the most promising
means to improve the cellular system capacity in the fifth-generation (5G) era. Compared …

Graph neural network (GNN) is an efficient neural network model for graph data and is
widely used in different fields, including wireless communications. Different from other …

In this paper, we surveyed the existing literature studying different approaches and
algorithms for the four critical components in the general branch and bound (B&B) algorithm …

With the growing popularity of the Internet-of-Vehicles (IoV), it is of pressing necessity to
understand transportation traffic patterns and their impact on wireless network designs and …

With the rapid development of mobile Internet, the demand for multicast is growing rapidly,
such as content pushing and video streaming. The multicast service is usually offered to …

The backscatter and active RF radios can complement each other and bring potential
performance gain. In this paper, we envision a dual-mode radio structure that allows each …

Internet of Things (IoT) services have been implemented for several network applications
from smart cities to rural areas. However, there are many barriers to provide an efficient …

The damage to cellular towers during natural and man-made disasters can disturb the
communication services for cellular users. One solution to the problem is using unmanned …