While the fifth-generation systems are being rolled out across the globe, researchers have
turned their attention to the exploration of radical next-generation solutions. At this early …

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

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

Reconfigurable intelligent surfaces (RISs) have received considerable attention as a key
enabler for envisioned 6G networks, for the purpose of improving the network capacity …

The rapid increase in data traffic caused by the proliferation of smart devices has spurred the
demand for extremely large-capacity wireless networks. Thus, faster data transmission rates …

Cloud computing platforms support the Internet of Vehicles, but the main bottlenecks are
high latency and massive data transmission in cloud-based processing. Vehicular fog …

Due to the increasing need for time with respect to industrial growth and the speeding up of
human day-to-day work, network evolution is always the center of focus for research …

Edge intelligence has arisen as a promising computing paradigm for supporting
miscellaneous smart applications that rely on machine learning techniques. While the …

The advancing applications based on machine learning and deep learning in
communication networks have been exponentially increasing in the system architectures of …

Graph neural networks (GNNs) are a class of deep learning algorithms that learn from
graphs, networks and relational data. They have found applications throughout the sciences …