4D Imaging in ISAC Systems: A Framework Based on 5G NR Downlink Signals

Fuente: arXiv
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Main Authors: Weng, Haoyang, Wu, Haisu, Ren, Hong, Pan, Cunhua, Wang, Jiangzhou
Format: Preprint
Published: 2025
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author Weng, Haoyang
Wu, Haisu
Ren, Hong
Pan, Cunhua
Wang, Jiangzhou
author_facet Weng, Haoyang
Wu, Haisu
Ren, Hong
Pan, Cunhua
Wang, Jiangzhou
contents Integrated sensing and communication (ISAC) has emerged as a key enabler for sixth-generation (6G) wireless networks, supporting spectrum sharing and hardware integration. Beyond communication enhancement, ISAC also enables high-accuracy environment reconstruction and imaging, which are crucial for applications such as autonomous driving and digital twins. This paper proposes a 4D imaging framework fully compliant with the 5G New Radio (NR) protocol, ensuring compatibility with cellular systems. Specifically, we develop an end-to-end processing chain that covers waveform generation, echo processing, and multi-BS point cloud fusion. Furthermore, we introduce Zoom-OMP, a coarse-to-fine sparse recovery algorithm for high-resolution angle estimation that achieves high accuracy with reduced computational cost. The simulation results demonstrate that the proposed framework achieves robust 4D imaging performance with superior spatial accuracy and reconstruction quality compared to conventional benchmarks, paving the way for practical ISAC-enabled environment reconstruction in 6G networks.
format Preprint
id arxiv_https___arxiv_org_abs_2511_04913
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle 4D Imaging in ISAC Systems: A Framework Based on 5G NR Downlink Signals
Weng, Haoyang
Wu, Haisu
Ren, Hong
Pan, Cunhua
Wang, Jiangzhou
Signal Processing
Integrated sensing and communication (ISAC) has emerged as a key enabler for sixth-generation (6G) wireless networks, supporting spectrum sharing and hardware integration. Beyond communication enhancement, ISAC also enables high-accuracy environment reconstruction and imaging, which are crucial for applications such as autonomous driving and digital twins. This paper proposes a 4D imaging framework fully compliant with the 5G New Radio (NR) protocol, ensuring compatibility with cellular systems. Specifically, we develop an end-to-end processing chain that covers waveform generation, echo processing, and multi-BS point cloud fusion. Furthermore, we introduce Zoom-OMP, a coarse-to-fine sparse recovery algorithm for high-resolution angle estimation that achieves high accuracy with reduced computational cost. The simulation results demonstrate that the proposed framework achieves robust 4D imaging performance with superior spatial accuracy and reconstruction quality compared to conventional benchmarks, paving the way for practical ISAC-enabled environment reconstruction in 6G networks.
title 4D Imaging in ISAC Systems: A Framework Based on 5G NR Downlink Signals
topic Signal Processing
url https://arxiv.org/abs/2511.04913