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IEICE Transactions on Communications
Online ISSN : 1745-1345
Print ISSN : 0916-8516
Regular Section
Welch FFT Segment Size Selection Method for Spectrum Awareness System
Hiroki IWATAKenta UMEBAYASHISamuli TIIROJanne J. LEHTOMÄKIMiguel LÓPEZ-BENÍTEZYasuo SUZUKI
Author information
  • Hiroki IWATA

    Department of Electrical Engineering, Tokyo University of Agriculture and Technology

  • Kenta UMEBAYASHI

    Department of Electrical Engineering, Tokyo University of Agriculture and Technology

  • Samuli TIIRO

    Department of Electrical Engineering, Tokyo University of Agriculture and Technology

  • Janne J. LEHTOMÄKI

    University of Oulu

  • Miguel LÓPEZ-BENÍTEZ

    Department of Electrical Engineering and Electronics, University of Liverpool

  • Yasuo SUZUKI

    Department of Electrical Engineering, Tokyo University of Agriculture and Technology

Corresponding author

ORCID
Keywords:cognitive radio,duty cycle,dynamic spectrum access,spectrum measurement,Welch FFT
JOURNALRESTRICTED ACCESS

2016 Volume E99.BIssue 8Pages 1813-1823

DOIhttps://doi.org/10.1587/transcom.2015EBP3401
Details
  • Published: August 01, 2016Manuscript Received: September 18, 2015Released on J-STAGE: August 01, 2016Accepted: -Advance online publication: -Manuscript Revised: April 01, 2016
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Abstract

We create a practical method to set the segment size of the Welch FFT for wideband and long-term spectrum usage measurements in the context of hierarchical dynamic spectrum access (DSA). An energy detector (ED) based on the Welch FFT can be used to detect the presence or absence of primary user (PU) signal and to estimate the duty cycle (DC). In signal detection with the Welch FFT,segment size is an important design parameter since it determines both the detection performance and the frequency resolution. Between these two metrics, there is a trade-off relationship which can be controlled by adjusting the segment size. To cope with this trade-off relationship, we define an optimum and, more easy to analyze sub-optimum segment size design criterion. An analysis of the sub-optimum segment size criterion reveals that the resulting segment size depends on the signal-to-noise ratio (SNR) and the DC. Since in practice both SNR and DC are unknown, proper segment setting is difficult. To overcome this problem, we propose an adaptive segment size selection (ASSS) method that uses noise floor estimation outputs. The proposed method does not require any prior knowledge on the SNR or the DC. Simulation results confirm that the proposed ASSS method matches the performance achieved with the optimum design criterion.

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© 2016 The Institute of Electronics, Information and Communication Engineers
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