Low-Complexity Near-Field Beam Training with DFT Codebook based on Beam Pattern Analysis
Fuente:
arXiv
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866908370988957696 |
|---|---|
| author | Wang, Zijun Kiran, Rama Tsai, Shawn Zhang, Rui |
| author_facet | Wang, Zijun Kiran, Rama Tsai, Shawn Zhang, Rui |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_21954 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Low-Complexity Near-Field Beam Training with DFT Codebook based on Beam Pattern Analysis Wang, Zijun Kiran, Rama Tsai, Shawn Zhang, Rui Signal Processing 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. |
| title | Low-Complexity Near-Field Beam Training with DFT Codebook based on Beam Pattern Analysis |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2503.21954 |