Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization
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Abstract (arXiv)
In the intelligent reflecting surface (IRS)-enhanced wireless communication system, channel state information (CSI) is of paramount importance for achieving the passive beamforming gain of IRS, which, however, is a practically challenging task due to its massive number of passive elements without transmitting/receiving capabilities. In this letter, we propose a practical transmission protocol to execute channel estimation and reflection optimization successively for an IRS-enhanced orthogonal frequency division multiplexing (OFDM) system. Under the unit-modulus constraint, a novel reflection pattern at the IRS is designed to aid the channel estimation at the access point (AP) based on the received pilot signals from the user, for which the channel estimation error is derived in closed-form. With the estimated CSI, the reflection coefficients are then optimized by a low-complexity algorithm based on the resolved strongest signal path in the time domain. Simulation results corroborate the effectiveness of the proposed channel estimation and reflection optimization methods.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Sep 2019.
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Citing papers per year: 2021: 3; 2022: 3; 2023: 1; 2024: 1; 2025: 1.
9 papers.
- 2023Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimizationcited by 56
- 2022MIMO Channel Estimation using Score-Based Generative Modelscited by 50
- 2022Pervasive Machine Learning for Smart Radio Environments Enabled by Reconfigurable Intelligent Surfacescited by 12
- 2022Deep Learning-Based Rate-Splitting Multiple Access for Reconfigurable Intelligent Surface-Aided Tera-Hertz Massive MIMOcited by 4
- 2021A Robust Deep Learning-Based Beamforming Design for RIS-assisted Multiuser MISO Communications with Practical Constraintscited by 3
- 2021Deep Learning Based RIS Channel Extrapolation with Element-groupingcited by 2
- 2024Deep-Learning Channel Estimation for IRS-Assisted Integrated Sensing and Communication Systemcited by 2
- 2025Channel Estimation for RIS-Assisted mmWave Systems via Diffusion Modelscited by 2
- 2021Untrained DNN for Channel Estimation of RIS-Assisted Multi-User OFDM System with Hardware Impairmentscited by 1
- 2025Channel Estimation for RIS-Assisted mmWave Systems via Diffusion Models9 Jun 2025
- 2024Deep-Learning Channel Estimation for IRS-Assisted Integrated Sensing and Communication System29 Jan 2024
- 2023Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization10 Aug 2023
- 2022Deep Learning-Based Rate-Splitting Multiple Access for Reconfigurable Intelligent Surface-Aided Tera-Hertz Massive MIMO18 Sep 2022
- 2022Pervasive Machine Learning for Smart Radio Environments Enabled by Reconfigurable Intelligent Surfaces8 May 2022
- 2022MIMO Channel Estimation using Score-Based Generative Models14 Apr 2022
- 2021A Robust Deep Learning-Based Beamforming Design for RIS-assisted Multiuser MISO Communications with Practical Constraints12 Nov 2021
- 2021Untrained DNN for Channel Estimation of RIS-Assisted Multi-User OFDM System with Hardware Impairments13 Jul 2021
- 2021Deep Learning Based RIS Channel Extrapolation with Element-grouping14 May 2021