Channel Estimation for BIOS-Assisted Multi-User MIMO Systems: A Heterogeneous Two-timescale Strategy

TL;DR

This paper proposes a novel two-timescale, sparsity-exploiting channel estimation scheme for BIOS-assisted multi-user MIMO systems, addressing the unique heterogeneous channel properties and reducing training overhead.

Contribution

It introduces a new channel estimation method tailored for BIOS's bilayer structure, leveraging manifold optimization and channel properties to improve efficiency.

Findings

Significantly reduces training overhead in BIOS systems

Achieves competitive channel estimation accuracy

Maintains BIOS performance advantage over IRS and IOS

Abstract

Bilayer intelligent omni-surface (BIOS) has recently attracted increasing attention due to its capability of independent beamforming on both reflection and refraction sides. However, its specific bilayer structure makes the channel estimation problem more challenging than the conventional intelligent reflecting surface (IRS) or intelligent omni-surface (IOS). In this paper, we investigate the channel estimation problem in the BIOS-assisted multi-user multiple-input multiple-output system. We find that in contrast to the IRS or IOS, where the forms of the cascaded channels of all user equipments (UEs) are the same, in the BIOS, those of the UEs on the reflection side are different from those on the refraction side, which is referred to as the heterogeneous channel property. By exploiting it along with the two-timescale and sparsity properties of channels and applying the manifold optimization method, we propose an efficient channel estimation scheme to reduce the training overhead in the BIOS-assisted system. Moreover, we investigate the joint optimization of base station digital beamforming and BIOS passive analog beamforming. Simulation results show that the proposed estimation scheme can significantly reduce the training overhead with competitive estimation quality, and thus keeps the performance advantage of BIOS over IRS and IOS with imperfect channel state information.