NSS-ML: a Novel spectrum sensing framework using machine learning for cognitive radio IoT networks
- Title
- NSS-ML: a Novel spectrum sensing framework using machine learning for cognitive radio IoT networks
- Creator
- Marriwala N.K.; Shukla V.K.; Shanbhog M.; Panda S.; Kaushik R.; Rathore D.
- Description
- A key component of cognitive radio systems is spectrum sensing, which reduces coexistence problems and maximises spectrum efficiency. However, the introduction of multiple situations with distinct characteristics brought about by 5G communication presents problems for spectrum sensing to support a wide range of applications with high performance and flexible implementation. Inspired by these difficulties, a new method with a multi-layer extreme learning machine optimised for bats is presented in this study. This technique makes use of a variety of input vectors, such as channel ID, energy, distance, and received signal intensity, to enhance user categorization and sensing capabilities. Moreover, we compare the proposed method with the state-of-the-art spectrum sensing approaches in order to evaluate its effectiveness in 5G situations, especially in healthcare applications. Evaluation metrics including channel detection probability, sensitivity, and selectivity are carefully examined. The findings unequivocally prove the suggested spectrum sensing approachs superiority over current methods and highlight its potential for smooth incorporation into a variety of 5G applications. Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.
- Source
- International Journal of Information Technology (Singapore), Vol-16, No. 7, pp. 4599-4604.
- Date
- 2024-01-01
- Publisher
- Springer Science and Business Media B.V.
- Subject
- 5G communications; BAT algorithm; Cognitive radio; Spectrum sensing
- Coverage
- Marriwala N.K., Dept. of Electronics and Communication Engineering, University Institute of Engineering and Technology, Kurukshetra University, Haryana, Kurukshetra, India; Shukla V.K., Information Technology Head of Academics-School of Engineering Architecture Interior Design, Amity University, Dubai, United Arab Emirates; Shanbhog M., School of Sciences, Christ (deemed to be university), Delhi NCR Campus, Uttar Pradesh, Ghaziabad, India; Panda S., Dept. of Electrical, Electronics and Communication Engineering, GITAM School of Technology, Bengaluru Campus, Karnataka, Doddaballapura, India; Kaushik R., Dept. of Electronics and Communication Engineering, University Institute of Engineering and Technology, Kurukshetra University, Haryana, Kurukshetra, India; Rathore D., Dept. of Electronics and Communication Engineering, Guru Ghasidas Vishwavidyalaya, Bilaspur, India
- Rights
- Restricted Access
- Relation
- ISSN: 25112104
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Marriwala N.K.; Shukla V.K.; Shanbhog M.; Panda S.; Kaushik R.; Rathore D., “NSS-ML: a Novel spectrum sensing framework using machine learning for cognitive radio IoT networks,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/12786.