Near-Field Beam Training Through Beam Diverging

As a key enabling technique for extremely largescale antenna array (ELAA), near-field (NF) beam training aims to estimate the channel conditions across all antenna-user equipment (UE) links, which is inherently complex and therefore challenging. Existing NF beam training methods primarily rely on beam focusing techniques, where numerous codewords that concentrate the signal beam on different points or directions are sequentially deployed as pilots to match the channel conditions, resulting in a trade-off between pilot overhead and beam training accuracy. In this paper, we introduce the concept of the beam diverging effect and leverage it to enable more efficient beam training. First, we propose the mirror codeword and demonstrate that it can trigger beam diverging effect using only one radio frequency (RF) chain. Then, we introduce the mirror polardomain codebook (MPC) along with a hierarchical method that enables rough localization of the UE using only $2 \log _{2} N$ pilots. Finally, we present two supplementary approaches to enhance beam training performance: a pilot set expansion method to enable precise beam training and an MPC angular range reduction method to ensure the effectiveness of the proposed algorithm. Numerical results affirm that our proposed algorithm achieves high beam training accuracy while using relatively low overhead.