Full-duplex spectrum sensing in cognitive radios using optical self-interference cancellation

Matthew P. Chang, Paul Richard Prucnal, Yanhua Deng

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

6 Scopus citations

Abstract

We propose and experimentally demonstrate an optical self-interference cancellation system to realize full-duplex spectrum sensing in cognitive radios. The optical system is an analog radio-frequency front-end module, which cancels in-band self-interference, enabling a radio to simultaneously transmit and receive signals. The system achieves 83 dB of narrowband interference cancellation, and 60 dB of cancellation of a 50 MHz frequency-modulated signal. The center frequency of the optical canceler is freely tunable across the radio frequency spectrum, limited only by the bandwidth of the photodetector and the electro-optic modulators to 10 GHz. The system is modulation-format independent and requires only one piece of hardware to operate across a wide radio-frequency bandwidth. By reducing self-interference to acceptably low powers, a cognitive radio can continuously sense its radio-frequency environment to detect the presence of a licensed user or scan for spectrum white spaces even while transmitting simultaneously.

Original languageEnglish (US)
Title of host publication2015 9th International Conference on Sensing Technology, ICST 2015
PublisherIEEE Computer Society
Pages341-344
Number of pages4
ISBN (Electronic)9781479963140
DOIs
StatePublished - Mar 21 2016
Event9th International Conference on Sensing Technology, ICST 2015 - Auckland, New Zealand
Duration: Dec 8 2015Dec 11 2015

Publication series

NameProceedings of the International Conference on Sensing Technology, ICST
Volume2016-March
ISSN (Print)2156-8065
ISSN (Electronic)2156-8073

Other

Other9th International Conference on Sensing Technology, ICST 2015
Country/TerritoryNew Zealand
CityAuckland
Period12/8/1512/11/15

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Signal Processing
  • Electrical and Electronic Engineering

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