Primary radio user activity models for cognitive radio networks: A survey
Abstract Cognitive Radio Networks have been emerged as a promising solution for solving
the problem of spectrum scarcity and improving spectrum utilization by opportunistic use of …
the problem of spectrum scarcity and improving spectrum utilization by opportunistic use of …
Predicting dynamic spectrum allocation: a review covering simulation, modelling, and prediction
The advent of the Internet of Things and 5G has further accelerated the growth in devices
attempting to gain access to the wireless spectrum. A consequence of this has been the …
attempting to gain access to the wireless spectrum. A consequence of this has been the …
Evaluation of the maintenance system readiness using the semi-Markov model taking into account hidden factors
Maintaining the proper level of readiness and reliability is crucial for any operating system
[33, 44]. It enables the purposeful use of the maintenance potential in the utilization …
[33, 44]. It enables the purposeful use of the maintenance potential in the utilization …
Statistical spectrum occupancy prediction for dynamic spectrum access: a classification
Spectrum scarcity due to inefficient utilisation has ignited a plethora of dynamic spectrum
access solutions to accommodate the expanding demand for future wireless networks …
access solutions to accommodate the expanding demand for future wireless networks …
Evaluation of machinery readiness using semi-Markov processes
This article uses Markov and semi-Markov models as some of the most popular tools to
estimate readiness and reliability. They allow to evaluate of both individual elements as well …
estimate readiness and reliability. They allow to evaluate of both individual elements as well …
Deep Learning Models for Spectrum Prediction: A Review
L Wang, J Hu, D Jiang, C Zhang, R Jiang… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
Spectrum prediction is a promising technique for improving spectrum exploitation in
cognitive radio networks (CRNs). Accurate spectrum prediction can assist in reducing the …
cognitive radio networks (CRNs). Accurate spectrum prediction can assist in reducing the …
Spectrum prediction using hidden Markov models for industrial cognitive radio
A Saad, B Staehle, R Knorr - 2016 IEEE 12th International …, 2016 - ieeexplore.ieee.org
Cognitive radio (CR) is a key enabler of wireless in industrial applications especially for
those with strict quality-of-service (QoS) requirements. The cornerstone of CR is spectrum …
those with strict quality-of-service (QoS) requirements. The cornerstone of CR is spectrum …
NS-2 based simulation framework for cognitive radio sensor networks
In this paper, we propose a simulation model for cognitive radio sensor networks (CRSNs)
which is an attempt to combine the useful properties of wireless sensor networks and …
which is an attempt to combine the useful properties of wireless sensor networks and …
Spectrum sensing for cognitive radio using blind source separation and hidden Markov model
Most of the radio frequency spectrum is not being utilized efficiently. The utilization can be
improved by including unlicensed users to exploit the radio frequency spectrum by not …
improved by including unlicensed users to exploit the radio frequency spectrum by not …
Whitespace prediction using hidden markov model based maximum likelihood classification
A Saad, HF Schepker, B Staehle… - 2019 IEEE 89th …, 2019 - ieeexplore.ieee.org
The cornerstone of cognitive systems is environment awareness which enables agile and
adaptive use of channel resources. Whitespace prediction based on learning the statistics of …
adaptive use of channel resources. Whitespace prediction based on learning the statistics of …