In this survey paper, we characterize the learning problem in cognitive radios (CRs) and
state the importance of artificial intelligence in achieving real cognitive communications …

This paper presents a systematic and comprehensive survey that reviews the latest research
efforts focused on machine learning (ML) based performance improvement of wireless …

The ability to intelligently utilize resources to meet the need of growing diversity in services
and user behavior marks the future of wireless communication systems. Intelligent wireless …

With the proliferation of wireless technologies and the ever-increasing growth in Internet of
Things (IoT) devices operating the license-free Industrial, Scientific, and Medical (ISM) band …

Data science or “data-driven research” is a research approach that uses real-life data to gain
insight about the behavior of systems. It enables the analysis of small, simple as well as …

Cognitive radio networks (CRNs) are networks of nodes equipped with cognitive radios that
can optimize performance by adapting to network conditions. Although various routing …

This paper presents an autonomous cognitive radio (CR) architecture, referred to as the
Radiobot. This model goes beyond adaptive radio systems to exploit the main ingredients of …

A cognitive transceiver is required to opportunistically use vacant spectrum resources
licensed to primary users. Thus, it relies on a complete adaptive behavior composed of …

In this paper, we propose a Bayesian non-parametric signal classification approach for
spectrum sensing in cognitive radios (CR's). The proposed classification approach is based …

Spectrum Sensing (SS) and Power Control (PC) have been two important concepts of
Cognitive Radio (CR). In this paper, a mechanism combining these two topics is proposed to …