Proceedings of the 2025 International Conference on Advanced Research in Electronics and Communication Systems (ICARECS-2025)

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Reducing Spectrum Sensing Overhead in Cognitive Radio Systems using CNN-LSTM for Primary User Traffic Prediction

Authors
D. Sumithra Sofia1, *, A. Shirly Edward2
1Department of ECE, St.Joseph’s College of Engineering, Semmencherri, Chennai, India
2Department of ECE, SRM Institute of Science and Technology, Vadapalani, Chennai, India
*Corresponding author. Email: sumithrasofiad@stjosephs.ac.in
Corresponding Author
D. Sumithra Sofia
Available Online 30 June 2025.
DOI
10.2991/978-94-6463-754-0_72How to use a DOI?
Keywords
DSA; CNN; DSS; Hack RF Radio; LSTM
Abstract

Time sensing is vital for the effective operation of cognitive radio systems. This paper presents a method for predicting primary user spectrum patterns to minimize battery consumption for cognitive users by reducing the need for continuous spectrum sensing. We have developed a CNN-LSTM-based model to improve the accuracy of traffic prediction. This methodology has been rigorously tested across various frequency bands utilized by existing mobile operators, employing deep radio techniques.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 International Conference on Advanced Research in Electronics and Communication Systems (ICARECS-2025)
Series
Atlantis Highlights in Engineering
Publication Date
30 June 2025
ISBN
978-94-6463-754-0
ISSN
2589-4943
DOI
10.2991/978-94-6463-754-0_72How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - D. Sumithra Sofia
AU  - A. Shirly Edward
PY  - 2025
DA  - 2025/06/30
TI  - Reducing Spectrum Sensing Overhead in Cognitive Radio Systems using CNN-LSTM for Primary User Traffic Prediction
BT  - Proceedings of the 2025 International Conference on Advanced Research in Electronics and Communication Systems (ICARECS-2025)
PB  - Atlantis Press
SP  - 827
EP  - 836
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-754-0_72
DO  - 10.2991/978-94-6463-754-0_72
ID  - Sofia2025
ER  -