Machine Learning Techniques in Cognitive Radio Networks

TL;DR

This paper reviews how machine learning techniques are applied to develop intelligent, adaptive cognitive radio networks that efficiently utilize spectrum resources by learning from their environment.

Contribution

It provides a comprehensive review of machine learning applications in cognitive radio networks, highlighting recent advancements and implementations.

Findings

Machine learning enables dynamic spectrum management.

Enhanced adaptability of cognitive radios through learning algorithms.

Improved spectrum utilization efficiency.

Abstract

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 devices that are capable of learning and adapting to their transmission to the external radio environment, which means it has some kind of intelligence for monitoring the radio environment, learning the environment and make smart decisions. In this paper, we are reviewing some examples of the usage of machine learning techniques in cognitive radio networks for implementing the intelligent radio.