Hiroki IWATA, Kenta UMEBAYASHI, Janne J. LEHTOMÄKI, Shusuke NARIEDA, Welch FFT Segment Size Selection Method for FFT Based Wide Band Spectrum Measurement, IEICE Transactions on Communications, 2018, Volume E101.B, Issue 7, Pages 1733-1743, Released July 01, 2018, [Advance publication] Released January 18, 2018, Online ISSN 1745-1345, Print ISSN 0916-8516, https://doi.org/10.1587/transcom.2017EBP3069
Welch FFT segment size selection method for FFT based wide band spectrum measurement
|Author:||Iwata, Hiroki1; Umebayashi, Kenta1; Lehtomäki, Janne J.2;|
1The authors are with Department of Electrical and Electronic Engineering, Tokyo University of Agriculture and Technology, Koganei-shi, 184-8588 Japan
2The author is with University of Oulu, P. O. BOX 4500 FIN- 90014, University of Oulu, Finland
3The author is with Department of Electrical and Computer Engineering, National Institute of Technology, Akashi College, Akashi-shi, 674-8501 Japan
|Online Access:||PDF Full Text (PDF, 1.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe201902155018
Institute of Electronics, Information and Communication Engineers,
|Publish Date:|| 2019-02-15
We introduce a Welch FFT segment size selection method for FFT-based wide band spectrum measurement in the context of smart spectrum access (SSA), in which statistical spectrum usage information of primary users (PUs), such as duty cycle (DC), will be exploited by secondary users (SUs). Energy detectors (EDs) based on Welch FFT can detect the presence of PU signals in a broadband environment efficiently, and DC can be estimated properly if a Welch FFT segment size is set suitably. There is a trade-off between detection performance and frequency resolution in terms of the Welch FFT segment size. The optimum segment size depends on signal-to-noise ratio (SNR) which makes practical and optimum segment size setting difficult. For this issue, we previously proposed a segment size selection method employing a relationship between noise floor (NF) estimation output and the segment size without SNR information. It can achieve accurate spectrum awareness at the expense of relatively high computational complexity since it employs exhaustive search to select a proper segment size. In this paper, we propose a segment size selection method that offers reasonable spectrum awareness performance with low computational complexity since limited search is used. Numerical evaluations show that the proposed method can match the spectrum awareness performance of the conventional method with 70% lower complexity or less.
IEICE transactions on communications. B
|Pages:||1733 - 1743|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This research and development work was supported by the MIC/SCOPE #165003006, and JSPS KAKENHI Grant Numbers JP15K06053, JP15KK0200.
© 2018 The Institute of Electronics, Information and Communication Engineers.