Cognitive radio networks (CRN) have gained great relevance in the efficient use of the radio
spectrum, and one of the key aspects of this technology is the spectral decision. The …

Recent developments in mobile network communication increases the usage of the cellular
users and their wideband data transfer. Sometimes, network operators may get overloaded …

Deep reinforcement learning is a successful learning model in many application domains. A
Cognitive radio network (CRN) is a promising solution for spectrum scarcity and sharing …

Cognitive radio networks (CRN) allow for an increase in spectral efficiency and performance
of today's wireless networks. Currently, multiple proposals exist in the area of spectral …

Emerging wireless applications needs more spectrums space to tackle the rapid growth of
users. Outside of radio band in spectrum will be hard to utilize for data transmissions in …

Cognitive Radio Networks (CRNs) have ushered in a transformative era in wireless
communication, resha** the landscape of radio spectrum utilization and management. At …

Cognitive radio networks promote better spectral efficiency of the electric radio spectrum.
The vast majority of current spectral decision models for cognitive radio networks evaluate …

A novel model regarding downlink cooperative non-orthogonal multiple access (NOMA) in
device-to-device network will be investigated in this paper, especially combining amplify …

The success of cognitive radio network (CRN) depends upon the accurate spectrum
sensing. The hidden and open terminal problems are serious threats in the way of reliable …

The concept of smart cities has gained considerable momentum in recent years, with
vehicular communication becoming a vital component of Intelligent Traffic Systems (ITS) …