Binary Intelligent Reflecting Surfaces Assisted OFDM Systems

Yashvanth, L and Murthy, CR and Battu, D (2022) Binary Intelligent Reflecting Surfaces Assisted OFDM Systems. In: 14th IEEE International Conference on Signal Processing and Communications, SPCOM 2022, 11 July 2022 through 15 July 2022.

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Abstract

Intelligent reflecting surfaces (IRSs) enhance the performance of wireless systems by reflecting the incoming signals towards a desired user, especially in the mmWave bands. However, this requires optimizing the discrete reflection coefficients of the IRS elements, which crucially depends on the availability of accurate channel state information (CSI) of all links in the system. Further, in wideband systems employing orthogonal frequency division multiplexing (OFDM), a given IRS configuration cannot be simultaneously optimal for all the subcarriers, and hence the phase optimization is not straightforward. In this paper, we propose a novel IRS phase configuration scheme in OFDM systems by first leveraging the sparsity of the channel in the angular domain to estimate the CSI using simultaneous orthogonal matching pursuit (SOMP) algorithm, and then devising a novel and computationally efficient binary IRS phase configuration algorithm using majorization-minimization (MM). Simulation results illustrate the efficacy of the approach in comparison with the state-of-the-art. © 2022 IEEE.

Item Type:	Conference Paper
Publication:	SPCOM 2022 - IEEE International Conference on Signal Processing and Communications
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to the IEEE.
Keywords:	Broadband networks; Orthogonal frequency division multiplexing, Channel-state information; Intelligent reflecting surface; Majorization-minimization; Minimisation; Orthogonal frequency division multiplexing systems; Orthogonal frequency-division multiplexing; Orthogonal matching pursuit; Reflecting surface; Simultaneous orthogonal matching pursuit; Surface phasis, Channel state information
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	06 Sep 2022 07:27
Last Modified:	06 Sep 2022 07:27
URI:	https://eprints.iisc.ac.in/id/eprint/76487

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