Terahertz (THz) is a promising technology for future wireless communication networks,
particularly for 6G and beyond. The ultra-wide THz band, ranging from 0.1 to 10 THz, can …

Artificial intelligence has made remarkable progress in handling complex tasks, thanks to
advances in hardware acceleration and machine learning algorithms. However, to acquire …

Wireless IoT networks have seen an unprecedented rise in number of devices,
heterogeneity and emerging use cases which led to diverse throughput, reliability and …

Supported by some of the major revolutionary technologies, such as Internet of Vehicles
(IoVs), Edge Computing, and Machine Learning (ML), the traditional Vehicular Networks …

Federated Learning (FL) offers collaborative machine learning without data exposure, but
challenges arise in the mobile edge network (MEC) environment due to limited resources …

The development of the 5G network and the transition to 6G has given rise to multiple
challenges for ensuring high-quality and reliable network services. One of these main …

Traditionally, non-terrestrial networks (NTNs) are used for a limited set of applications, such
as TV broadcasting and communication support during disaster relief. Nevertheless, due to …

The 6G communication technologies are expected to provide fast data rates and incessant
connectivity to heterogeneous networks, such as the Internet of Vehicles (IoV). However, the …

Achieving sustainable freight transport and citizens' mobility operations in modern cities are
becoming critical issues for many governments. By analyzing big data streams generated …

With the advent of 6G technology, the proliferation of interconnected devices necessitates a
robust, fully connected intelligence network. Federated Learning (FL) stands as a key …