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The rapid advancements in 5G technologies have created an unprecedented need for efficient spectrum utilization to support increasing data traffic and diverse communication services. In this context, accurate and reliable spectrum sensing is essential. This study explores wideband spectrum sensing strategies, comparing non-cooperative cognitive radio (CR) techniques with cooperative methods across multiple subbands. A novel cooperative wideband spectrum sensing framework was developed, incorporating a K-outof-N fusion rule at the fusion center to make optimal decisions by selecting an appropriate K for a given number of cooperating CRs. This approach addresses noise uncertainty, a common challenge in traditional non-cooperative energy detection methods, particularly in 5G environments under Additive White Gaussian Noise (AWGN) conditions, assumed to be identically and independently distributed (i.i.d.). However, while cooperative sensing significantly improves detection in low signal-to-noise ratio (SNR) scenarios with higher false alarm rates (between 0.5 and 1), our findings reveal that it does not consistently outperform non-cooperative methods at very low false alarm rates (0.01 and 0.1) under poor SNR conditions. These findings highlight the need for further research to enhance cooperative sensing strategies for various operational environments.
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This content will become publicly available on July 19, 2026
THE EFFECTS OF DIVERSITY SCHEMES ON ENHANCINGENERGY DETECTOR-BASED COOPERATIVE WIDEBAND SPECTRUM SENSING IN 5G NETWORKS
The proliferation of 5G technologies and the vast deployment of Internet of Things (IoT) devices have heightened the demand for optimal spectrum utilization, necessitating robust spectrum management strategies. In this context, an efficient energy detector employing wideband spectrum sensing within a 5G environment is essential for identifying underutilized frequency bands suitable for cognitive radio applications across multiple subbands. While cooperative spectrum sensing (CSS) can enhance the detection capabilities of energy detectors amidst noise uncertainty, its performance often deteriorates under low signal-to-noise ratio (SNR) conditions. This study proposes an improved CSS framework that combines Maximal Ratio Combining (MRC) with the K-out-of-N fusion rule to address noise uncertainty in a complex Gaussian environment across multiple sub-bands in cooperative wideband spectrum sensing. Comparative performance analysis confirms that this integrated approach enhances detection probability and maintains a low false alarm rate across various low SNR scenarios, significantly outperforming traditional cooperative and non-cooperative wideband spectrum sensing methods. These results highlight the potential for advancing cognitive radio technologies by optimizing detection algorithms to improve performance under challenging conditions.
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- Award ID(s):
- 2306236
- PAR ID:
- 10629158
- Editor(s):
- Wyld, David C; Nagamalai, Dhinaharan
- Publisher / Repository:
- CS&IT
- Date Published:
- Volume:
- 15
- Issue:
- 13
- ISSN:
- 2231-5403
- ISBN:
- 978-1-923107-64-9
- Page Range / eLocation ID:
- 119-128
- Subject(s) / Keyword(s):
- Signal-Noise Ratio, Maximal Ratio Combining Wideband Spectrum Sensing Energy Detection K-out-of-N fusion rule
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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