Real-Time Multi-Target Detection and Tracking with mmWave 5G NR Waveforms on RFSoC

Fuente: arXiv
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Autores principales: Li, Xinyang, Voon, Hian Zing, Andrei, Vlad C., Sessler, Alexander, Sciammetta, Nunzio, Mönich, Ullrich J., Schupke, Dominic A., Boche, Holger
Formato: Preprint
Publicado: 2025
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author Li, Xinyang
Voon, Hian Zing
Andrei, Vlad C.
Sessler, Alexander
Sciammetta, Nunzio
Mönich, Ullrich J.
Schupke, Dominic A.
Boche, Holger
author_facet Li, Xinyang
Voon, Hian Zing
Andrei, Vlad C.
Sessler, Alexander
Sciammetta, Nunzio
Mönich, Ullrich J.
Schupke, Dominic A.
Boche, Holger
contents We demonstrate a real-time implementation of multi-target detection and tracking using 5G New Radio (NR) physical downlink shared channel (PDSCH) waveform with 400 MHz bandwidth at 28 GHz carrier frequency. The hardware platform is built on a radio frequency system-on-chip (RFSoC) 4x2 board connected with a pair of Sivers EVK02001 mmWave beamformers for transmission and reception. The entire sensing transceiver processing and fast beam control are realized purely in the programmable logic (PL) part of the RFSoC, enabling low-latency and fully hardware-accelerated operation. The continuously acquired sensing data constitute 3D range-angle (RA) tensors, which are processed on a host PC using adaptive background subtraction, cell-averaging constant false alarm rate (CA-CFAR) detection with density-based spatial clustering of applications with noise (DBSCAN) clustering, and extended Kalman filtering (EKF), to detect and track targets in the environment. Our software-defined radio (SDR) testbed integrates heterogeneous computing resources, including CPUs, GPUs, and FPGAs, thereby providing design flexibility for a wide range of tasks.
format Preprint
id arxiv_https___arxiv_org_abs_2512_22582
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Real-Time Multi-Target Detection and Tracking with mmWave 5G NR Waveforms on RFSoC
Li, Xinyang
Voon, Hian Zing
Andrei, Vlad C.
Sessler, Alexander
Sciammetta, Nunzio
Mönich, Ullrich J.
Schupke, Dominic A.
Boche, Holger
Signal Processing
We demonstrate a real-time implementation of multi-target detection and tracking using 5G New Radio (NR) physical downlink shared channel (PDSCH) waveform with 400 MHz bandwidth at 28 GHz carrier frequency. The hardware platform is built on a radio frequency system-on-chip (RFSoC) 4x2 board connected with a pair of Sivers EVK02001 mmWave beamformers for transmission and reception. The entire sensing transceiver processing and fast beam control are realized purely in the programmable logic (PL) part of the RFSoC, enabling low-latency and fully hardware-accelerated operation. The continuously acquired sensing data constitute 3D range-angle (RA) tensors, which are processed on a host PC using adaptive background subtraction, cell-averaging constant false alarm rate (CA-CFAR) detection with density-based spatial clustering of applications with noise (DBSCAN) clustering, and extended Kalman filtering (EKF), to detect and track targets in the environment. Our software-defined radio (SDR) testbed integrates heterogeneous computing resources, including CPUs, GPUs, and FPGAs, thereby providing design flexibility for a wide range of tasks.
title Real-Time Multi-Target Detection and Tracking with mmWave 5G NR Waveforms on RFSoC
topic Signal Processing
url https://arxiv.org/abs/2512.22582