Multi-Resolution Codebook-Based Beam Training for RIS Beamforming: Design and Experiments

Reconfigurable intelligent surface (RIS) has emerged as a promising solution to enable ultra-massive multiple-input multiple-output (MIMO) for 6G wireless communications. To reduce pilot overhead, multi-resolution codebook-based beam training has been proposed for RIS-aided communication systems. However, the hardware constraints of the RIS such as the limited control capability, mutual coupling, and manufacturing tolerances have not been fully considered, which may result in non-ideal beam patterns and misleading beam search directions, thereby degrading the overall beam training performance. To address this issue, in this paper, we revisit the multi-resolution codebook design and beam training scheme by taking the RIS hardware constraints into account. First, we propose a wide-beam generation method via multi-beam superposition, where the RIS reflection coefficients are optimized to achieve high beam gain with minimal fluctuations. Then, a posterior-based beam training scheme is proposed to adaptively correct erroneous beam search directions, thereby improving the beam training accuracy. We implement a prototype RIS with 32x32 reflective elements and deploy a 26 GHz millimeter-wave RIS-aided wireless communication testbed to experimentally evaluate the proposed scheme. The results indicate that our approach achieves low training overhead and a data rate close to the exhaustive search method.