We consider the problem of dynamic platoon leader selection, user association, channel
assignment, and power allocation on a cellular vehicle-to-everything (C-V2X) based …

Recently, in order to improve the service quality of cloud-based services, research on a
reinforcement learning model that predicts an appropriate amount of cloud resources by …

In this paper, we present an approach for resource scheduling in wireless networks based
on the Network Slicing (NS) paradigm using Double Deep Q-Network (DDQN) …

Assume that an interferer behaves according to a parametric model but one does not know
the value of the model parameters. Sensing enables to improve the model knowledge and …

Continuing exponential surge in mobile data traffic demands the need for heterogeneous
networks (HetNets) in which low-power nodes small cells such as picocells and femtocells …

With the introduction of machine learning (ML) technologies, the development of wireless
access networks has gained more significant momentum, enabling WiFi and radio access …

Machine learning has found many applications in network contexts. These include solving
optimisation problems and managing network operations. Conversely, networks are …

The emergence of 5G networks has increased the demand for network resources, making
efficient resource management crucial. Slice admission control (SAC) is a process that …

This thesis considers the power allocation (PA) to maximize the achievable sum-rate in
hybrid beamforming (HB) multi-user massive multiple-input multiple-output (MU-mMIMO) …

Next-generation networks, such as those beyond 5th generation (B5G) and 6th generation
(6G) generation, have diverse network resource demands that imply significant changes in …