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Experimental Evaluation of 5G NR OFDM-Based Passive Radar Exploiting Reference, Control, and User Data.

Marek Wypich^1,2, Tomasz P Zielinski¹

¹Faculty of Computer Science, Electronics and Telecommunications, Institute of Telecommunications, AGH University of Krakow, al. A. Mickiewicza 30, 30-059 Krakow, Poland.

Sensors (Basel, Switzerland)

|February 27, 2026

Summary

This study experimentally shows that using user data from 5G downlink signals in passive radar significantly improves sensing performance. Incorporating more signal components enhances detection probability and peak height compared to pilot-only methods.

Keywords:

5G New Radio (NR)OFDM radar bit error rate (BER)channel frequency response (CFR)delay-Doppler map (DDM)illumination of opportunity integrated sensing and communication (ISAC)passive radar reference signals user data payloads

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Area of Science:

Integrated Sensing and Communication (ISAC)
Wireless Communication Systems
Signal Processing

Background:

Passive radars in communication-centric ISAC systems leverage existing communication signals for sensing.
Orthogonal frequency division multiplexing (OFDM)-based passive radars typically use reference signals for channel frequency response (CFR) estimation.
Prior simulations suggest performance gains by incorporating user data into CFR estimation.

Purpose of the Study:

To experimentally evaluate an OFDM-based passive radar utilizing all components of the 5G New Radio (NR) downlink waveform.
To assess the impact of using user data and various downlink channels on sensing performance.
To analyze the effect of partial knowledge of data locations and bit error rate (BER) on performance.

Main Methods:

Experimental evaluation of an OFDM-based passive radar system.
Joint utilization of synchronization signals (PSS, SSS), control channels (PBCH, PDCCH), data channels (PDSCH), and reference signals (DM-RS, CSI-RS) from 5G NR downlink.
Estimation of transmission bit error rate (BER) and analysis of its impact.
Investigation of scenarios with partial knowledge of PDSCH resource element locations.

Main Results:

Utilizing user data from fully occupied 5G downlink signals significantly improves probability of detection (POD) and peak-to-noise-floor ratio (PNFR) compared to pilot-only sensing.
Performance gains are observed under the assumption of full knowledge of Physical Downlink Shared Channel (PDSCH) locations.
Analysis quantifies the impact of BER and partial data location knowledge on sensing performance.

Conclusions:

Jointly utilizing all 5G NR downlink waveform components, especially user data, enhances passive radar sensing performance.
Partial knowledge of data locations and varying BER conditions present realistic challenges that affect performance.
The findings support the integration of user data for improved passive radar capabilities in 5G systems.