Advanced search ?

Object

Deep Learning-based SNR Estimation for Multistage Spectrum Sensing in Cognitive Radio Networks, Journal of Telecommunications and Information Technology, 2022, nr 4
Download

Title: Deep Learning-based SNR Estimation for Multistage Spectrum Sensing in Cognitive Radio Networks, Journal of Telecommunications and Information Technology, 2022, nr 4

Creator:

Patil, Vilaskumar ; Jeevangi, Sanjeevkumar ; Jawaligi, Shivkumar

Date:

2022, nr 4

Resource Type:

artykuł

Description:

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 of CR applications. Therefore, a new multi-stage detector for robust signal and spectrum sensing applications is introduced here. Initially, the sampled signal is subjected to SNR estimation by using a convolutional neural network (CNN). Next, the detection strategy is selected in accordance with the predicted SNR levels of the received signal. Energy detector (ED) and singular value-based detector (SVD) are the solutions utilized in the event of high SNR, whilst refined non-negative matrix factorization (MNMF) is employed in the case of low SNR. CNN weights are chosen via the Levy updated sea lion optimization (LU-SLNO) algorithm inspired by the traditional sea lion optimization (SLNO) approach. Finally, the outcomes of the selected detectors are added, offering a precise decision on spectrum tenancy and existence of the signal.

Publisher:

Instytut Łączności - Państwowy Instytut Badawczy

Format:

application/pdf

Resource Identifier:

oai:bc.itl.waw.pl:2248 ; ISSN 1509-4553, on-line: ISSN 1899-8852

DOI:

10.26636/jtit.2022.164922

eISSN:

1899-8852

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

cognitive radio spectrum sensing optimized CNN improved NMF LU-SLNO system

Object collections:

Last modified:

Jun 6, 2024

In our library since:

Feb 7, 2023

Number of object content hits:

36

All available object's versions:

https://bc.itl.waw.pl/publication/2557

Show description in RDF format:

RDF

Show description in OAI-PMH format:

OAI-PMH

Edition name Date
Jawaligi, Shivkumar, Deep Learning-based SNR Estimation for Multistage Spectrum Sensing in Cognitive Radio Networks, Journal of Telecommunications and Information Technology, 2022, nr 4 Jun 6, 2024

Objects Similar
Optimal Voting Rule and Minimization of Total Error Rate in Cooperative Spectrum Sensing for Cognitive Radio Networks, Journal of Telecommunications and Information Technology, 2021, nr 1

Bachan, P. Trankatwar, Sachin Ravikant Ghosh, Samit Kumar

2021, nr 1
artykuł
Optimization of Spectrum Sensing Parameters in Cognitive Radio Using Adaptive Genetic Algorithm, Journal of Telecommunications and Information Technology, 2017, nr 1

Roy, Jibendu Sekhar Bhattacharya, Partha Pratim Dutta, Swaham Chatterjee, Subhajit

2017, nr 1
artykuł
Suboptimal Approach to Distributed Detection in Cognitive Radio Networks, Journal of Telecommunications and Information Technology, 2021, nr 1

Kumari, Shweta Praveena, Sirimilla

2021, nr 1
artykuł
2023, nr 3, JTIT-artykuły
2023, nr 3, JTIT-artykuły
An Efficient Cooperative Spectrum Sensing Method Using Renyi Entropy Weighted Optimal Likelihood Ratio for CRN, Journal of Telecommunications and Information Technology, 2023, nr 3

Poshattiwar, Sadhana D. Shrote, Sandip B.

2023, nr 3
artykuł
Mobility-Aware, Correlation-Based Node Grouping and Selection for Cooperative Spectrum Sensing, Journal of Telecommunications and Information Technology, 2014, nr 2

Bogucka, Hanna Benedetto, Maria Gabriella Di Cichoń, Krzysztof Nardis, Luca De

2014, nr 2
artykuł
Cooperative Spectrum Sensing in Cognitive Radio Networks: A Survey on Machine Learning-based Methods, Journal of Telecommunications and Information Technology, 2020, nr 3

Khamayseh, Sundous Halawani, Alaa

2020, nr 3
artykuł
Optimal Spectrum Sensor Assignment in Multi-channel Multi-user Cognitive Radio Networks, Journal of Telecommunications and Information Technology, 2018, nr 4

K. S., Nandini Hariprasad, S. A.

2018, nr 4
artykuł
Implementation of Selected Spectrum Sensing Systems for Cognitive Radio Networks using FPGA Platform, Journal of Telecommunications and Information Technology, 2018, nr 4

Abdullah, Hikmat N. Abed, Hadeel S.

2018, nr 4
artykuł
More
×

Citation

Citation style:

Contact details

Address

Instytut Łączności – Państwowy Instytut Badawczy ul. Szachowa 1 04-894 Warszawa

Phone

(+48) 5128 696

E-Mail

biblioteka@il-pib.pl

Visit us!

This page uses 'cookies'. More information