Deep Neural Network Architectures for Spectrum Sensing Using Signal Processing Features

SS Chandra, A Upadhye, P Saravanan… - 2021 IEEE …, 2021 - ieeexplore.ieee.org
In this work, we consider a performance comparison of deep learning-based approaches to
the problem of spectrum sensing (SS) in cognitive radios. Towards this end, we use signal …

Eigenvalue-based spectrum sensing in cognitive radio networks using supervised learning

G Krishnan, N Joshi, HMB Shankar… - … on Internet of …, 2021 - ieeexplore.ieee.org
We consider supervised machine learning-based detection algorithms for spectrum sensing
in cognitive radio (CR) networks. The network comprises of multiple CR nodes, which collect …

On spectrum sensing, a machine learning method for cognitive radio systems

Y Arjoune, N Kaabouch - 2019 IEEE International Conference …, 2019 - ieeexplore.ieee.org
Spectrum sensing plays an important role in enabling cognitive radio technology for the up-
and-coming generation of wireless communication systems. Over the last decade, several …

Comparison of neural network architectures for spectrum sensing

Z Ye, A Gilman, Q Peng, K Levick… - 2019 IEEE …, 2019 - ieeexplore.ieee.org
Different neural network (NN) architectures have different advantages. Convolutional neural
networks (CNNs) achieved enormous success in computer vision, while recurrent neural …

[HTML][HTML] Analysis of spectrum sensing using deep learning algorithms: CNNs and RNNs

A Kumar, N Gaur, S Chakravarty, MH Alsharif… - Ain Shams Engineering …, 2024 - Elsevier
Spectrum sensing is a critical component of cognitive radio systems, enabling the detection
and utilization of underutilized frequency bands. Convolutional neural networks (CNNs) and …

A performance comparison of spectrum sensing exploiting machine learning algorithms

P Nimudomsuk, M Sanguanwattanaraks… - 2021 18th …, 2021 - ieeexplore.ieee.org
Machine learning is the powerful tool of the artificial intelligence which is popularly
implemented in several applications. Spectrum sensing is the important function of a …

Machine-learning-based spectrum sensing enhancement for software-defined radio applications

S AGHABEIKI, C HALLET… - 2021 IEEE cognitive …, 2021 - ieeexplore.ieee.org
The Software-defined radio (SDR) technology is considered as a promising solution to
address the issue of spectrum scarcity by providing a high level of flexibility and …

A supervised learning approach for differential entropy feature-based spectrum sensing

P Saravanan, SS Chandra, A Upadhye… - 2021 Sixth …, 2021 - ieeexplore.ieee.org
In this work, we consider a supervised machine learning-based approach for spectrum
sensing in cognitive radios. The noise process is assumed to follow a generalized Gaussian …

Cognitive radio spectrum sensing and prediction using deep reinforcement learning

SQ Jalil, S Chalup, MH Rehmani - 2021 International Joint …, 2021 - ieeexplore.ieee.org
In this paper, we propose to use deep reinforcement learning (DRL) for the task of
cooperative spectrum sensing (CSS) in a cognitive radio network. We selected a recently …

Deep Learning-based SNR Estimation for Multistage Spectrum Sensing in Cognitive Radio Networks

S Jeevangi, S Jawaligi, V Patil - Journal of Telecommunications and …, 2022 - jtit.pl
Vacant frequency bands are used in cognitive radio (CR) by incorporating the spectrum
sensing (SS) technique. Spectrum sharing plays a central role in ensuring the effectiveness …