Speaker
Description
Integrated Sensing and Communications (ISAC) is an emerging technology that enables wireless systems to support both communication and sensing functions. This paper presents a software-defined radio (SDR) proof-of-concept for detecting indoor human motion using 5G New Radio (NR) signals, with GNU Radio serving as the software platform for implementing the transceiver and signal processing. The proposed setup consists of a 5G transmitter and a dual-antenna receiver that captures both a reference signal and reflections from moving targets.
We investigate the use of 5G Synchronization Signal Blocks (SSB) and Zadoff-Chu (ZC) sequences as sensing waveforms. A simple signal processing chain is implemented to mitigate strong direct-path and static environmental signals that can obscure target reflections. The processing pipeline includes adaptive Least Mean Squares (LMS) filtering for interference suppression, background-clutter cancellation, and range-Doppler estimation using cross-correlation and FFT-based processing.
The system is evaluated through simulation, wired loopback testing, and over-the-air indoor experiments involving human movement. Results demonstrate successful suppression of dominant interference components and the generation of clear range-Doppler maps for moving targets. The implementation highlights practical design considerations and computational trade-offs for real-time SDR-based sensing.
By focusing on accessible algorithms and open-source tools, this work provides a low-complexity and reproducible framework for exploring 5G-based sensing applications in GNU Radio.
| Talk Length | N/A |
|---|---|
| Link to Open Source Code | https://github.com/krishna-kanth-r/GRcon26_SDR_passive_radar |
| Acknowledge | Acknowledge In-Person |