Multi-agent reinforcement learning (MARL) has become a fundamental component of next-
generation wireless communication systems. Theoretically, although MARL has the …

Reconfigurable wireless network can flexibly provide efficient spectrum access service and
keep stable operation in highly dynamic environment. In this paper, a primary-prioritized …

We all know that wireless communication plays a crucial role in the success of high-speed
rail operation. If we apply cognitive radio (CR) technology to individual in high-speed rail, it …

The rapid development of artificial intelligence (AI) techniques has triggered a revolution in
beyond fifth-generation (B5G) and upcoming sixth-generation (6G) mobile networks. Despite …

In this study, reinforcement learning algorithms are compared in TORCS simulation
environment. In this simulation environment, the goal is to finish the track as soon as …

The radio spectrum is witnessing a major paradigm shift from fixed spectrum assignment
policy to the dynamic spectrum access, which will completely change the way radio …

Deep learning has recently emerged as a disruptive technology to solve challenging radio
resource management problems in wireless networks. However, the neural network …

The future cellular networks are expected to support an increasing number of users with
heterogeneous applications, requiring varying network resources. Therefore, the 6G and …

Resource allocation is of great importance in the next generation wireless communication
systems, especially for cognitive radio networks (CRNs). Many resource allocation strategies …

Cognitive radio is an intelligent radio that can be programmed and configured dynamically
to fully use the frequency resources that are not used by licensed users. It defines the radio …