Downlink ISAC with a Full-Stack 5G-Compliant Experimental Testbed: Communication vs. Control Signals for Multi-Target Detection

Integrated Sensing and Communication (ISAC) is envisioned as a key enabler for 5G and beyond mobile networks. While numerous theoretical works have demonstrated its potential, experimental studies employing 5G-compliant waveforms and full-stack implementations remain limited. In this work, we investigate monostatic downlink ISAC using a sub-6 GHz, full-stack, 5G-compliant experimental testbed built with software-defined radios, an advanced channel emulator, and the open source OpenAirInterface5G framework. We specifically compare the use of communication and control signals for multi-target detection. To this end, we develop a complete digital signal processing pipeline, encompassing the acquisition and temporal alignment of the TX/RX I/Q samples, followed by matched-filter or channel-estimation-like processing, and multi-target detection on the resulting range–Doppler maps. To mitigate the issue of erroneous multiple detections for a same dominant lobe, we propose a clustering strategy that effectively reduces false alarms while enhancing visibility of dominant targets. Experimental results reveal excellent sensing performance when communication signals are employed, owing to their larger bandwidth and longer transmission duration. Nevertheless, meaningful sensing is also obtained via control signals, which, despite their reduced information, have the notable advantage of continuous availability (always-on) even in the absence of active users.