Extremely large antenna arrays (ELAAs) operating in high-frequency bands have spurred the development of near-field communication, driving advancements in beam training design. This paper introduces an efficient near-field beam training method that utilizes the discrete Fourier transform (DFT) codebook traditionally employed for far-field users (FUs). We begin by analyzing the received beam pattern and deriving closed-form expressions for its width and central beam gain as a function of user location. Building on these derived expressions, we propose a beam training method that estimates user distance from the received signal powers using DFT beams, with a computational complexity of O(1). Simulation results confirm the efficacy of our approach, demonstrating its ability to perform low-complexity near-field beam training with high estimation accuracy. Notably, our proposed scheme achieves up to a 1.96 dB SNR gain over exhaustive search methods in multi-user beamforming scenarios.
@article{arxiv.2503.21954,
title = {Low-Complexity Near-Field Beam Training with DFT Codebook based on Beam Pattern Analysis},
author = {Zijun Wang and Rama Kiran and Shawn Tsai and Rui Zhang},
journal= {arXiv preprint arXiv:2503.21954},
year = {2025}
}