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arXiv · 2408.09592

Near-Field Sensing: A Low-Complexity Wavenumber-Domain Method

Hao Jiang·Zhaolin Wang·Yuanwei Liu
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Abstract

A novel low-complexity wavenumber-domain method is proposed for near-field sensing (NISE). Specifically, the power-concentrated region of the wavenumber-domain channels is related to the target position in a non-linear manner. Based on this observation, a bi-directional convolutional neural network (BiCNN)-based approach is proposed to capture such a relationship, thereby facilitating low-complexity target localization. This method enables direct and gridless target localization using only a limited bandwidth and a single antenna array. Simulation results demonstrate that: 1) during the offline training phase, the proposed BiCNN method can learn to localize the target with fewer trainable parameters compared to the naive neural network architectures; and 2) during the online implementation phase, the BiCNN method can spend 100x less time while maintaining comparable performance to the conventional two-dimensional multiple signal classification (MUSIC) algorithms.

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Hao Jiang, Zhaolin Wang, Yuanwei Liu. 2024-08-18. Near-Field Sensing: A Low-Complexity Wavenumber-Domain Method. https://arxiv.org/abs/2408.09592

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