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SαS noise suppression for OFDM wireless communication in rayleight channel

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

DOI
10.11591/ijece.v10i2.pp2003-2010
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

Orthogonal frequency division multiplexing (OFDM) is a form of multi-carrier transmission technique widely used in the modern wireless network to achieve high-speed data transmission with good spectral efficiency. However, in impulsive noise environement BER performances of these systems, originally designed for a Gaussian noise model, are much degraded. In this paper, a new symmetric-alpha-stable (SαS) noise suppression technique based conjointly on adaptive modulation, convolutional coding (AMC) and Recursive Least Square (RLS) filtering is presented. The proposed scheme is applied on OFDM system in Rayleigh fading channel. The transmissions are analyzed under different combinations of digital modulation schemes (BPSK, QPSK, 16-QAM, 64-QAM) and convolutional code rates (1/2, 2/3, 3/4). Simulation results show that our proposed hybrid technique provides effective impulsive noise cancelation in OFDM system and exhibits better BER performance.

Collaboration network of the authors

7 authors · 9 co-authorship links · 2 across different organisations

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  • University of Abou Bekr Belkaïd
  • University of Leicester
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Sidi Mohammed Hadj IridUniversity of Abou Bekr Belkaïd1
Saïd AssousUniversity of Leicester1
Ibrahim Yassine NoualiAffiliation unknown1
Zohra SlimaneAffiliation 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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