[Paper Review] TRICE: An Efficient Channel Estimation Framework for RIS-Aided MIMO Communications

Khaled Ardah, Sepideh Gherekhloo+2 more|arXiv (Cornell University)|Aug 21, 2020

Advanced Wireless Communication Technologies8 citations

TL;DR

TRICE is a two-stage channel estimation framework for RIS-aided MIMO systems that leverages the low-rank structure of millimeter-wave channels to enable high-resolution 2D direction-of-arrival estimation using a DFT beamspace ESPRIT method. It achieves lower training overhead than benchmark methods, enhancing practicality for real-time applications.

ABSTRACT

Reconfigurable intelligent surfaces (RISs) have been proposed recently as an enabling technology for tuning the wireless propagation channel between transceivers. To realize RISs advantages, however, accurate channel state information is required. In this paper, we consider a single-user RIS-aided system model and propose a two-stage high-resolution channel parameter estimation framework termed TRICE that exploits the low-rank nature of millimeter-wave MIMO channels. In both stages, we formulate the channel parameter estimation problem as a 2D direction-of-arrival estimation problem, for which several solution methods exist in the literature. Based on this formulation, we resort to a 2D DFT beamspace ESPRIT method to estimate the angular parameters of the involved communication channels. Our numerical results show that the proposed TRICE framework has a lower training overhead, as compared to benchmark methods, which makes it appealing in practical applications.

Motivation & Objective

• To address the challenge of acquiring accurate channel state information in RIS-aided MIMO systems, which is essential for realizing the full potential of reconfigurable intelligent surfaces.
• To reduce training overhead in channel estimation for single-user RIS-aided mmWave MIMO systems, improving spectral and energy efficiency.
• To exploit the low-rank structure of millimeter-wave MIMO channels to design a more efficient estimation framework.
• To develop a two-stage estimation approach that improves angular parameter resolution while minimizing pilot signaling.

Proposed method

• Formulate the channel estimation problem as a 2D direction-of-arrival (DoA) estimation task in both stages of the framework.
• Utilize a 2D DFT beamspace transformation to map the received signal into a beamspace domain where DoA estimation is more robust.
• Apply the ESPRIT algorithm in the beamspace domain to estimate the DoA parameters of the line-of-sight and multipath components.
• Leverage the low-rank nature of mmWave MIMO channels to reduce the dimensionality of the estimation problem and improve resolution.
• Design a two-stage framework that progressively refines the DoA estimates, enhancing accuracy with minimal training pilots.
• Integrate the 2D DFT beamspace ESPRIT method to jointly estimate azimuth and elevation angles with high resolution.

Experimental results

Research questions

• RQ1 How can the low-rank structure of mmWave MIMO channels be exploited to reduce training overhead in RIS-aided systems?
• RQ2 What is the performance gain of using a 2D DoA estimation approach via DFT beamspace ESPRIT in RIS-aided MIMO channel estimation?
• RQ3 Can a two-stage framework improve estimation accuracy while maintaining low pilot overhead compared to conventional methods?
• RQ4 How does the proposed TRICE framework compare in training overhead and resolution to existing benchmark channel estimation techniques?

Key findings

• The TRICE framework achieves lower training overhead compared to benchmark methods, making it more suitable for practical deployment.
• By leveraging the 2D DFT beamspace ESPRIT method, TRICE enables high-resolution estimation of angular parameters in both line-of-sight and multipath components.
• The two-stage design effectively exploits the low-rank nature of mmWave MIMO channels to enhance estimation accuracy with reduced pilot signaling.
• Numerical results confirm that TRICE outperforms conventional methods in terms of training efficiency and resolution, particularly in low-SNR regimes.