NDLI: Data clustering algorithm for channel segmentation in a radio monitoring system

Content Provider	IET Digital Library
Author	Weber, Christian Peter, Martin Felhauer, Tobias Christ, Andreas Schuessele, Lothar
Abstract	The detection of signals and the estimation of signal bandwidth is a perpetual topic in radio communication systems. Both issues are extremely challenging, since the wireless channel is unreliable in nature. A radio monitoring system faces the most difficult conditions in this task; it normally scans a wide frequency range of several hundred MHz and has to detect a multitude of different signals. Owing to the computational costs, the radio monitoring systems use nowadays mainly energy detectors based on fast Fourier transform spectrum analysers and a static threshold, defined by a previous noise estimation. A refined algorithm based on the self-splitting competitive learning (SSCL) clustering is presented that quantises the power spectral density (PSD) according to the present signal power levels. The quantisation of the PSD results in a promising channel segmentation. In contrast to the traditional threshold evaluation, this approach is independent of a previously assumed noise estimation and therefore more robust against noise level and noise distribution changes. The presented definition of the essential cluster validity criterion is key for a successful channel segmentation. Furthermore, the novel postprocessing of the clustering result introduced in this study evaluates the progression of the PSD data and significantly improves the channel segmentation.
Starting Page	3308
Ending Page	3317
Page Count	10
ISSN	17518628
Volume Number	8
e-ISSN	17518636
Issue Number	Issue 18, Dec (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/8/18
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2013.1104
Journal	IET Communications
Publisher Date	2014-12-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Channel Segmentation Cluster Validity Criterion Cognitive Radio Cognitive Radio Device Data Clustering Algorithm Energy Detector Fast Fourier Transform Fast Fourier Transform Spectrum Analysers Integral Transforms Learning in AI Monitoring Noise Estimation Pattern Clustering Power Spectral Density PSD Quantisation Quantisation (signal) Radio Link And Equipment Radio Monitoring System Self-splitting Competitive Learning Clustering Signal Bandwidth Estimation Signal Detection Spectral Analysis Threshold Evaluation Wireless Channel Wireless Communication System
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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