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A combined spectrum sensing method based DCT for cognitive radio system

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 10 No. 2 (2020)

DOI
10.11591/ijece.v10i2.pp1935-1942
ISSN
2088-8708, 2088-8708
Published
2020-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

In this paper a new hybrid blind spectrum sensing method is proposed. The method is designed to enhance the detection performance of Conventional Energy Detector (CED) through combining it with a proposed sensing module based on Discrete Cosine Transform (DCT) coefficient’s relationship as operation mode at low Signal to Noise Ratio (SNR) values. In the proposed sensing module a certain factor called Average Ratio (AR) represent the ratio of energy in DCT coefficients is utilized to identify the presence of the Primary User (PU) signal. The simulation results show that the proposed method improves PU detection especially at low SNR values.

Collaboration network of the authors

6 authors · 7 co-authorship links · 3 across different organisations

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  • Nahrain University
  • National University of Malaysia
  • Mustansiriyah University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Haider A. H. AlobaidyNational University of Malaysia1
Tariq M. SalmanMustansiriyah University1
Thamir Rashed SaeedAffiliation unknown1
Asaad Hameed SaharAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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