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:最近,由于在反射和反折面上独立波束成形的能力,双层结构使频道估算问题比常规智能反射表面(IRS)或智能全表(IOS)更具挑战性。在本文中,我们调查了BIOS协助的多用户多输入多输出系统中的频道估算问题。我们发现,与IRS或IOS不同的是,所有用户设备(UES)的级联渠道形式在BIOS相同,反射面的双层结构使频道估算问题比常规智能反射表面(IRS)或智能全表面(IOS)的问题更具有挑战性。我们研究了BIOS协助的多用户多输出系统(多输入多输出系统)中的频道估算问题。我们发现,与IRS或IOS辅助系统(IOS)中所有用户设备(UES)的分级化渠道形式相同,我们调查了基础站数字成型和BIOS被动模拟系统(IOS)反向反向反射面显示反射面特性,因此通过利用双向级系统(Simmassimpalation)系统的拟议业绩评估计划可以大大降低IIS的升级。