State-of-the-art energy detection (ED) based spectrum sensing requires perfect knowledge
of noise power and is vulnerable to noise uncertainty. An eigenvalue-based spectrum …

In this paper, we proposed the unscented Kalman filter (UKF) based on cooperative
spectrum sensing (CSS) scheme in a cognitive radio network (CRN) using an adaptive fuzzy …

In view of the issue that the single-signal symbol rate estimation methods are unsuitable for
time–frequency overlapped signals in underlay cognitive radio network (CRN), a novel …

Chapter 4 explores the scope of artificial intelligence in cognitive radio (CR)-based
scenarios for the internet of things (IoT) networks. The demand for more data rates for …

In blind signal detection, exact roll-off factor estimation needs to be performed for matched
filtering, but the performance of the present methods is far from satisfactory. Considering this …

Spectrum sensing (SS) is the important functions of cognitive radio networks (CRNs) which
decides whether the band or sub-band of spectrum is available or not for secondary users …

Spectrum sensing (SS) is one of the key functions of cognitive radio networks (CRNs)
whether the band or sub-band of spectrum is available or not for secondary users (SUs) ie …

The main objective of the thesis is to devise a reliable non-cooperative spectrum sensing
system that is able to detect noise-like signals. We harness the strength of cepstral analysis …

Motivated by the spectrum scarcity problem, Cognitive Radios (CRs) have been proposed
as a solution to opportunistically communicate over unused spectrum licensed to Primary …

This work focuses on the spectrum sensing for the case of non-identical noise levels among
antennas in cognitive radio systems. In this scenario, conventional eigenvalue-based …