Experimental investigation of signal sensing with overlapped FFT based energy detection

Ryo Takai, Shoya Uchida, Akihiro Sato, Mamiko Inamori, Yukitoshi Sanada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Overlapped FFT based energy detection has been proposed as a signal detection scheme in dynamic spectrum access. The overlapped FFT scheme increases the number of FFT frames to reduce the variance of squared noise and improve the detection probability. Though theoretical analysis and computer simulation of the overlapped FFT scheme have been carried out in the previous studies, it has not been investigated through experiments. This paper evaluates the performance of the energy detection with overlapped FFT through experiments. In the experiments, different from the assumption in computer simulation of previous researches, a fixed distortion component caused by a direct current (DC) offset is observed. Numerical results obtained through the experiments show that the overlapped FFT scheme improves the detection probability by up to 0.15 with the noise and the fixed distortion component. Moreover, the overlapped FFT scheme is also effective on indoor channel models under the existence of the fixed distortion component.

Original languageEnglish
Title of host publicationISPACS 2013 - 2013 International Symposium on Intelligent Signal Processing and Communication Systems
Pages225-229
Number of pages5
DOIs
Publication statusPublished - 2013
Event2013 21st International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2013 - Naha, Okinawa, Japan
Duration: 2013 Nov 122013 Nov 15

Publication series

NameISPACS 2013 - 2013 International Symposium on Intelligent Signal Processing and Communication Systems

Other

Other2013 21st International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2013
Country/TerritoryJapan
CityNaha, Okinawa
Period13/11/1213/11/15

ASJC Scopus subject areas

  • Artificial Intelligence
  • Signal Processing

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