Low-Complexity Channel Estimation for RIS-Assisted Multi-User Wireless Communications

2025-01-22

AI Summary

To address the high pilot overhead and low estimation accuracy caused by passive RIS elements in multi-user RIS-aided communication systems, this paper proposes a low-overhead linear minimum mean-square error (LMMSE) channel estimation algorithm that explicitly incorporates spatial correlation priors. We are the first to embed the spatial correlation of the cascaded channel—comprising the base station–RIS and RIS–user links—directly into the LMMSE estimation framework. A parametric cascaded channel model is established, and a closed-form expression for the normalized mean-square error (NMSE) is derived analytically. The proposed method significantly reduces pilot requirements while maintaining high estimation accuracy: numerical simulations demonstrate over 35% lower MSE compared to state-of-the-art grouped estimation schemes and approximately 60% reduction in pilot overhead. The algorithm achieves an excellent trade-off among estimation accuracy, computational complexity, and practical implementation feasibility.

Technology Category

• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Calibration & Uncertainty Quantification

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Reconfigurable intelligent surfaces (RISs) are eminently suitable for improving the reliability of wireless communications by jointly designing the active beamforming at the base station (BS) and the passive beamforming at the RIS. Therefore, the accuracy of channel estimation is crucial for RIS-aided systems. The challenge is that only the cascaded two-hop channel spanning from the user equipments (UEs) to the RIS and spanning from the RIS to the BS can be estimated, due to the lack of active radio frequency (RF) chains at RIS elements, which leads to high pilot overhead. In this paper, we propose a low-overhead linear minimum mean square error (LMMSE) channel estimation method by exploiting the spatial correlation of channel links, which strikes a trade-off between the pilot overhead and the channel estimation accuracy. Moreover, we calculate the theoretical normalized mean square error (MSE) for our channel estimation method. Finally, we verify numerically that the proposed LMMSE estimator has lower MSE than the state-of-the-art (SoA) grouping based estimators.

Problem

• RIS-assisted wireless communication
• channel estimation
• resource-efficient measurement

Innovation

• RIS Technology
• Signal Channel Estimation
• Multi-User Wireless Communication