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Intelligent Reflecting Surface OFDM Communication with Deep Neural Prior

Fireaizen, Tomer (author)
Techn Israel Inst Technol, Signal & Image Proc Lab SIPL, Fac Elect & Comp Engn, Haifa, Israel.
Metzer, Gal (author)
Tel Aviv Univ, Fac Engn, Tel Aviv, Israel.
Ben-David, Dan (author)
Techn Israel Inst Technol, Signal & Image Proc Lab SIPL, Fac Elect & Comp Engn, Haifa, Israel.
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Moshe, Yair (author)
Techn Israel Inst Technol, Signal & Image Proc Lab SIPL, Fac Elect & Comp Engn, Haifa, Israel.
Cohen, Israel (author)
Techn Israel Inst Technol, Signal & Image Proc Lab SIPL, Fac Elect & Comp Engn, Haifa, Israel.
Björnson, Emil, Professor, 1983- (author)
Linköpings universitet,KTH,Kommunikationssystem, CoS,Linköping Univ, Dept Elect Engn ISY, Linköping, Sweden.,Tekniska fakulteten,KTH Royal Insitute Technol, Sweden
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Techn Israel Inst Technol, Signal & Image Proc Lab SIPL, Fac Elect & Comp Engn, Haifa, Israel Tel Aviv Univ, Fac Engn, Tel Aviv, Israel. (creator_code:org_t)
Institute of Electrical and Electronics Engineers (IEEE), 2022
2022
English.
In: IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781538683477 - 9781538683484 ; , s. 2645-2650
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • An Intelligent Reflecting Surface (IRS) is an emerging technology for improving the data rate over wireless channels by controlling the underlying channel. In this paper, we describe a novel solution for IRS configuration to maximize the data rate over wideband channels. The optimization is obtained by online training of a deep generative neural network. Inspired by related works in image processing, this network is randomly initialized and acts as a regularization term for the optimization process since the structure of the generator is sufficient to capture a great deal of IRS statistics prior to any learning. In contrast to recent deep learning techniques for IRS configuration, the proposed technique does not require an offline training stage and can adapt quickly to any environment. Compared to the previous state-of-the-art algorithm, the proposed method is significantly faster and obtains IRS configurations that achieve higher data transmission rates.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Telekommunikation (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Telecommunications (hsv//eng)

Keyword

Intelligent reflecting surface (IRS)
Reconfigurable Intelligent Surface (RIS)
passive beamforming
OFDM
deep neural prior

Publication and Content Type

ref (subject category)
kon (subject category)

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