Problem
Research questions and friction points this paper is trying to address.
near-field channel estimation
beam training
spherical waves
training overhead
Hierarchical Beam Training and Codebook Design for Movable Antenna-Assisted Near-Field Systems
🤖 AI Summary
本文针对近场信道估计问题，提出一种基于可移动天线的分层波束训练策略及相应码本设计，有效降低训练开销并提高波束增益。
📝 Abstract
As sixth-generation (6G) communication systems evolve toward higher frequency bands and larger array apertures, the near-field range expands rapidly, making near-field channel estimation increasingly important and challenging. Beam training has been recognized as an effective approach for channel state information (CSI) acquisition. However, because of the propagation characteristics of spherical waves, beam training needs to perform a joint search in the angle and distance domains, which results in unaffordable beam training overhead. By flexibly reconfiguring antenna positions, movable antenna (MA) technology can fully exploit the spatial variations of wireless channels and achieve more accurate beam focusing, thereby providing additional flexibility for efficient beam training design. Therefore, based on MA-assisted near-field systems, we develop a hierarchical beam training strategy that combines reduced training overhead with high beam gain and design a corresponding hierarchical codebook. This codebook forms focused beams over the joint angle-distance domain, maximizing beam gain within the target region while suppressing energy leakage into non-target regions. Simulation results confirm substantial performance gains of the method over the conventional fixed-position antenna (FPA) system and the far-field beam training method.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Hierarchical Beam Training
Movable Antenna (MA)
Near-Field Systems
Codebook Design
Angle-Distance Domain
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