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.

翻译：双层智能全表面（BIOS）因其在反射和折射侧均具备独立波束赋形能力而近来受到广泛关注。然而，其特殊的双层结构使得信道估计问题比传统智能反射面（IRS）或智能全表面（IOS）更加具有挑战性。本文研究了BIOS辅助的多用户多输入多输出系统中的信道估计问题。我们发现，与IRS或IOS中所有用户设备（UE）级联信道形式相同不同，在BIOS中，反射侧UE与折射侧UE的级联信道具有差异，称之为异构信道特性。通过利用这一特性以及信道的双时间尺度和稀疏特性，并应用流形优化方法，我们提出了一种高效的信道估计方案，以降低BIOS辅助系统中的训练开销。此外，我们还研究了基站数字波束赋形与BIOS无源模拟波束赋形的联合优化。仿真结果表明，所提估计方案能以具有竞争力的估计质量显著降低训练开销，从而在信道状态信息不完善的情况下保持BIOS相对于IRS和IOS的性能优势。