Channel Estimation for RIS-Aided mmWave MIMO Channels

Abstract

A reconfigurable intelligent surface (RIS) can shape the radio propagation by passively changing the directions of impinging electromagnetic waves. The optimal control of the RIS requires perfect channel state information (CSI) of all the links connecting the base station (BS) and the mobile station (MS) via the RIS. Thereby the channel (parameter) estimation at the BS/MS and the related message feedback mechanism are needed. In this paper, we adopt a two-stage channel estimation scheme for the RIS-aided millimeter wave (mmWave) MIMO channels using an iterative reweighted method to sequentially estimate the channel parameters. We evaluate the average spectrum efficiency (SE) and the RIS beamforming gain of the proposed scheme and demonstrate that it achieves high-resolution estimation with the average SE comparable to that with perfect CSI.

5 pages, 6 figures, invited paper for IEEE SPAWC

References in corpus (5)

• An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems
• Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems
• Beyond Massive-MIMO: The Potential of Positioning with Large Intelligent Surfaces
• Compressive channel estimation and tracking for large arrays in mm wave picocells
• Radio Localization and Mapping with Reconfigurable Intelligent Surfaces

Cited by in corpus (7)

• Intelligent Reflecting Surface Aided Wireless Communications: A Tutorial
• Reconfigurable Intelligent Surface-Empowered MIMO Systems
• Channel Estimation for RIS-assisted Millimeter-wave MIMO Systems
• Channel Estimation for RIS-Aided mmWave MIMO Systems via Atomic Norm Minimization
• Channel Estimation and Hybrid Architectures for RIS-Assisted Communications
• Cascaded Channel Estimation for RIS Assisted mmWave MIMO Transmissions
• Learning to Estimate RIS-Aided mmWave Channels