Second-order cyclostationarity-based detection and classification of LTE SC-FDMA signals for cognitive radio

Jerjawi, Walid (2014) Second-order cyclostationarity-based detection and classification of LTE SC-FDMA signals for cognitive radio. Masters thesis, Memorial University of Newfoundland.

[img] [English] PDF (Migrated (PDF/A Conversion) from original format: (application/pdf)) - Accepted Version
Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.

Download (5Mb)
  • [img] [English] PDF - Accepted Version
    Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.
    (Original Version)

Abstract

Cognitive radio (CR) was developed for utilizing the spectrum bands efficiently. Spectrum sensing and awareness represent main tasks of a CR, providing the possibility of exploiting the unused bands. In this thesis, we investigate the detection and classification of Long Term Evolution (LTE) single carrier-frequency division multiple access (SC-FDMA) signals, which are used in uplink LTE, with applications to cognitive radio. We explore the second-order cyclostationarity of the LTE SC-FDMA signals, and apply results obtained for the cyclic autocorrelation function to signal detection and classification (in other words, to spectrum sensing and awareness). The proposed detection and classification algorithms provide a very good performance under various channel conditions, with a short observation time and at low signal-to-noise ratios, with reduced complexity. The validity of the proposed algorithms is verified using signals generated and acquired by laboratory instrumentation, and the experimental results show a good match with computer simulation results.

Item Type: Thesis (Masters)
URI: http://research.library.mun.ca/id/eprint/6445
Item ID: 6445
Additional Information: Includes bibliographical references (pages 75-78).
Department(s): Engineering and Applied Science, Faculty of
Date: May 2014
Date Type: Submission
Library of Congress Subject Heading: Signal processing; Cognitive radio networks; Long-Term Evolution (Telecommunications); Frequency division multiple access; Cyclostationary waves; Multiple Signal Classification

Actions (login required)

View Item View Item

Downloads

Downloads per month over the past year

View more statistics