Mobile devices such as smartphones and autonomous vehicles increasingly rely on deep
neural networks (DNNs) to execute complex inference tasks such as image classification …

Over the years, the Internet has been enriched with new available communication
technologies, for both fixed and mobile networks and devices, exhibiting an impressive …

Emerging vehicular applications with strict latency and reliability requirements pose high
computing requirements, and current vehicles' computational resources are not adequate to …

Cellular networks have evolved to support high peak bitrates with low loss rates as observed
by the higher layers. However, applications and services running over cellular networks are …

In today's data networks, the main protocol used to ensure reliable communications is the
transmission control protocol (TCP). The TCP performance is largely determined by the used …

As the complexity of Deep Neural Network (DNN) models increases, their deployment on
mobile devices becomes increasingly challenging, especially in complex vision tasks such …

Emerging wireless systems target to provide multi-Gbps data rates for each user, which can
be achieved by utilizing ultra-wide channels available at mmWave, terahertz, and lightwave …

Since Facebook was renamed Meta, a lot of attention, debate, and exploration have
intensified about what the Metaverse is, how it works, and the possible ways to exploit it. It is …

Although mission-critical applications require the use of deep neural networks (DNNs), their
continuous execution at mobile devices results in a significant increase in energy …

Future 5G/6G wireless networks will be increasingly using millimeter waves (mmWaves),
where fast and efficient beamforming is vital for providing continuous service to highly …