ISAC 4D Imaging System Based on 5G Downlink Millimeter Wave Signal

TL;DR

This paper introduces a novel 4D imaging method using 5G millimeter wave signals that improves sensing accuracy and efficiency for smart city applications, overcoming limitations of traditional FMCW-based techniques.

Contribution

The paper presents a 4D imaging approach based on 2D-FFT and 2D-MUSIC with a MIMO array design, along with a multi-dimensional CFAR detection algorithm, enhancing ISAC sensing performance.

Findings

Higher sensing accuracy demonstrated in simulations

Improved imaging resolution over FMCW methods

Reduced computational complexity in signal processing

Abstract

Integrated Sensing and Communication(ISAC) has become a key technology for the 5th generation (5G) and 6th generation (6G) wireless communications due to its high spectrum utilization efficiency. Utilizing infrastructure such as 5G Base Stations (BS) to realize environmental imaging and reconstruction is important for promoting the construction of smart cities. Current 4D imaging methods utilizing Frequency Modulated Continuous Wave (FMCW) based Fast Fourier Transform (FFT) are not suitable for ISAC scenarios due to the higher bandwidth occupation and lower resolution. We propose a 4D (3D-Coordinates, Velocity) imaging method with higher sensing accuracy based on 2D-FFT with 2D-MUSIC utilizing standard 5G Downlink (DL) millimeter wave (mmWave) signals. To improve the sensing precision we also design a transceiver antenna array element arrangement scheme based on MIMO virtual aperture technique. We further propose a target detection algorithm based on multi-dimensional Constant False Alarm (CFAR) detection, which optimizes the ISAC imaging signal processing flow and reduces the computational pressure of signal processing. Simulation results show that our proposed method has better imaging results. The code is publicly available at https://github.com/MrHaobolu/ISAC\_4D\_IMaging.git.