Channel Estimation for Optical Intelligent Reflecting Surface-Assisted VLC System: A Joint Space-Time Sampling Approach

TL;DR

This work addresses CSI acquisition for optical intelligent reflecting surface (OIRS)–assisted VLC under an alignment-based channel model. It develops a coherence-guided framework that exposes spatial and temporal coherence characteristics, deriving coherence distance $d_c$ and coherence time $t_c$ to guide estimation. A GO-based non-uniform codebook enables fast beam alignment, while a joint space-time sampling (JSTS) algorithm performs sequential subarray CSI estimation followed by 3D interpolation to recover full CSI within each coherence interval. Numerical results show that the proposed codebook matches or exceeds uniform-codebook performance with substantially fewer beams and that JSTS achieves significant CSI-overhead reductions with controllable NMSE, enabling practical OIRS-VLC deployments. The approach combines geometry-driven beamforming, temporal/spatial coherence, and interpolation to deliver efficient, scalable OIRS-assisted VLC channel estimation.

Abstract

Optical intelligent reflecting surface (OIRS) has attracted increasing attention due to its capability of overcoming signal blockages in visible light communication (VLC), an emerging technology for the next-generation advanced transceivers. However, current works on OIRS predominantly assume known channel state information (CSI), which is essential to practical OIRS configuration. To bridge such a gap, this paper proposes a new and customized channel estimation protocol for OIRSs under the alignment-based channel model. Specifically, we first unveil OIRS spatial and temporal coherence characteristics and derive the coherence distance and the coherence time in closed form. Next, to achieve fast beam alignment over different coherence time, we propose to dynamically tune the rotational angles of the OIRS reflecting elements following a geometric optics-based non-uniform codebook. Given the above beam alignment, we propose an efficient joint space-time sampling-based algorithm to estimate the OIRS channel. In particular, we divide the OIRS into multiple subarrays based on the coherence distance and sequentially estimate their associated CSI, followed by a spacetime interpolation to retrieve full CSI for other non-aligned transceiver antennas. Numerical results validate our theoretical analyses and demonstrate the efficacy of our proposed OIRS channel estimation scheme as compared to other benchmark schemes.

Figures (13)

• Figure 1: The channel model of the OIRS-reflected VLC path.
• Figure 2: Normalized magnitude curves versus AoD for RF IRS and OIRS.
• Figure 3: Diagram of the proposed OIRS channel estimation protocol.
• Figure 4: Comparison between different OIRS codebook designs and distributions of codewords in the detection plane.
• Figure 5: Sequential OIRS channel estimation.