Cognitive radio networks (CRNs) implementing spectrum sharing between primary and
secondary users are able to provide a needed solution for the increasing spectrum scarcity …

With the rapid development of wireless communication technology, the low utilization of
spectrum resources and the high demand for spectrum have always been an urgent and …

Machine learning (ML) techniques have gained significant attention in the field of cognitive
radio networks (CRNs) due to their ability to learn and adapt to changing environments. In …

Wireless Communication Network (WSN) applications are growing drastically daily, and
their extensive nature attracts researchers and development authorities. The critical issues …

Abstract In cognitive radio, Reinforcement Learning (RL) has been widely applied to the
construction of cognition engine. However, two crucial challenges remain to be resolved …

In this paper, an underlay cognitive radio network with energy harvesting is considered
which works in slotted mode. SU decides to transmit data or harvest energy from …

Deep reinforcement learning has recorded remarkable performance in diverse application
areas of artificial intelligence: pattern recognition, robotics, object segmentation …

Cognitive radio (CR) is the solution for the current spectral underutilized problems, Context
awareness and environment awareness are the key functions of CR nowadays. A software …

Abstract Cognitive Radio (CR) and Cooperative Communication provide key technologies
for efficient utilization of available unused spectrum bands (called resources) to achieve a …

Abstract Development of 5G technology and Internet of Things (IoT) devices has resulted in
higher bandwidth requirements leading to increased scarcity of wireless spectrum. Cognitive …