University of Oulu

M. López-Benítez, J. Lehtomäki, K. Umebayashi and D. Patel, "Accurate Noise Floor Calibration based on Modified Expectation Maximisation of Gaussian Mixture," 2019 IEEE Wireless Communications and Networking Conference (WCNC), Marrakesh, Morocco, 2019, pp. 1-6. doi: 10.1109/WCNC.2019.8885661

Accurate noise floor calibration based on modified expectation maximisation of Gaussian mixture

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Author: López-Benítez, Miguel1,2; Lehtomäki, Janne3; Umebayashi, Kenta4;
Organizations: 1Department of Electrical Engineering and Electronics, University of Liverpool, United Kingdom
2ARIES Research Centre, Antonio de Nebrija University, Spain
3Centre for Wireless Communications, University of Oulu, Finland
4Graduate School of Engineering, Tokyo University of Agriculture and Technology, Japan
5School of Engineering and Applied Science, Ahmedabad University, India
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.2 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019121949044
Language: English
Published: Institute of Electrical and Electronics Engineers, 2019
Publish Date: 2019-12-19
Description:

Abstract

An accurate estimation of the noise floor is of paramount importance for an optimum performance of spectrum sensing in Cognitive Radio (CR). The most common approach followed by existing noise floor estimation methods is to attempt to isolate a set of noise-only samples based on a given energy/power threshold. However, this approach is unreliable and in general unable to provide accurate estimations of the noise floor, in particular under low SNR conditions where the power of the Primary User (PU) signal is comparable to the noise floor of the CR device. In this context, this work considers a different approach where the power observed by the CR device is modelled as a Gaussian mixture. Based on a mathematical analysis of the relation among the parameters of the obtained Gaussian mixture, a modified version of the well-known Expectation Maximisation (EM) algorithm is proposed to fit the Gaussian mixture to the observed power values and provide an estimation of the noise floor, something that the general EM algorithm fails to achieve in this scenario. The obtained results demonstrate that the proposed method provides a highly accurate estimation of the noise floor in the presence of PU signals over the whole range of SNR values.

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Series: IEEE Wireless Communications and Networking Conference
ISSN: 1525-3511
ISSN-E: 1558-2612
ISSN-L: 1525-3511
ISBN: 978-1-5386-7646-2
ISBN Print: 978-1-5386-7647-9
Pages: 1 - 6
DOI: 10.1109/WCNC.2019.8885661
OADOI: https://oadoi.org/10.1109/WCNC.2019.8885661
Host publication: 2019 IEEE Wireless Communications and Networking Conference (WCNC), 15-18 April 2019, Marrakesh, Morocco
Conference: IEEE Wireless Communications and Networking Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: This work was supported by British Council under UKIERI DST Thematic Partnerships 2016-17 (ref. DST-198/2017). The work of J. Lehtomäki was supported by the Academy of Finland 6Genesis Flagship (grant 318927) and Infotech Oulu. The work of K. Umebayashi was supported in part by the MIC/SCOPE under Grant 165003006, and in part by the JSPS KAKENHI under Grant JP15K06053 and Grant JP15KK0200.
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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