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

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, where each sensing BS jointly estimates the three spatial coordinates and the BS-referenced radial velocity of each observed scatterer, ensuring direct compatibility with practical cellular deployments. 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. Simulation results demonstrate that the proposed framework achieves robust 4D parameter estimation performance together with superior spatial reconstruction quality compared to conventional benchmarks.