University of Oulu

H. Iwata, K. Umebayashi, A. Al-Tahmeesschi and J. Lehtomäki, "High-Efficiency FCME-Based Noise Power Estimation for Long-Term and Wide-Band Spectrum Measurements," in IEEE Access, vol. 9, pp. 149883-149893, 2021, doi: 10.1109/ACCESS.2021.3124905

High-efficiency FCME-based noise power estimation for long-term and wide-band spectrum measurements

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Author: Iwata, Hiroki1; Umebayashi, Kenta1; Al-Tahmeesschi, Ahmed1;
Organizations: 1Graduate School of Engineering, Tokyo University of Agriculture and Technology, Koganei 184-8588, Japan
2Centre for Wireless Communications, University of Oulu, 90014 Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.1 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2022020818003
Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2022-02-08
Description:

Abstract

Statistics in terms of spectrum occupancy are useful for efficient and smart dynamic spectrum sharing, and the statistics can be obtained by long-term and wide-band spectrum measurements. In this paper, we investigate noise floor (NF) estimation for energy detection (ED)-based long-term and wide-band spectrum measurements since the NF estimation heavily affects the ED performance and eventually the accuracy of the statistics in terms of spectrum occupancy. Specifically, we address the following NF estimation problems simultaneously for the first time in the spectrum measurement field: (1) slow time-varying property of the NF, (2) frequency dependency of the NF, (3) the NF estimation in the presence of the signal, and (4) the computational cost of the NF estimation. Firstly, we apply Forward consecutive mean excision (FCME) algorithm-based NF estimation to deal with the above three problems ((1), (2) and (3)) successfully. Second, we propose and apply an NF level change detection on top of the FCME algorithm-based NF estimation to deal with the fourth problem. The proposed NF level change detection exploits the slow time-varying property of the NF. Specifically, only if the significant NF level change is detected, the FCME algorithm-based NF estimation is performed to reduce the redundant NF estimations. In numerical evaluations, we show the efficiency and the validity of the NF level change detection for the NF estimation problems, and compare the NF estimation performance with the method without the NF level change detection.

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Series: IEEE access
ISSN: 2169-3536
ISSN-E: 2169-3536
ISSN-L: 2169-3536
Volume: 9
Pages: 149883 - 149893
DOI: 10.1109/ACCESS.2021.3124905
OADOI: https://oadoi.org/10.1109/ACCESS.2021.3124905
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: This work was supported in part by the European Commission in the framework of the H2020-EUJ-02-2018 project 5GEnhance under Grant 815056, in part by the ‘‘Strategic Information and Communications R&D Promotion Programme (SCOPE)’’ of Ministry of Internal Affairs and Communications (MIC) of Japan under Grant JPJ000595, in part by the Japan Society for the Promotion of Science (JSPS) KAKENHI under Grant JP18K04124 and Grant JP18KK0109, and in part by the Institute of Global Innovation Research in Tokyo University of Agriculture and Technology. The work of Janne Lehtomäki was supported by the Academy of Finland 6Genesis Flagship under Grant 318927, and in part by the Infotech Oulu.
EU Grant Number: (815056) 5G-Enhance - 5G Enhanced Mobile Broadband Access Networks in Crowded Environments
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
Copyright information: © The Author(s) 2021. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
  https://creativecommons.org/licenses/by/4.0/