Neyman Pearson Detector for Multiple Ambient Backscatter Zero-Energy-Devices Beacons using Near-Perfect Code

Recently, a novel ultra-low power indoor localization system based on Zero-Energy-Devices (ZEDs) has shown promising results in ambient backscatter communication. While prior work has demonstrated single-tag detection using a Neyman-Pearson (NP) framework, detecting multiple coexisting ZEDs remains a challenge due to signal interference and synchronization ambiguity. This paper introduces a new detection scheme designed specifically for multiple-ZED scenarios. We adopt the Near-Perfect Code (NPC) as a synchronization sequence, offering improved peak-to-side-lobe (PSL) performance to enhance distinguishability between concurrent tags. The proposed detection model builds upon the NPC framework, incorporating a contrast-based metric and multi-frequency combining to identify secondary ZEDs under controlled false alarm constraints. Experimental evaluations, conducted on the CorteXlab testbed massouri2014cortexlab, which is a part of the SLICES-EU European infrastructure. confirm the robustness of the model. In particular, the system demonstrates reliable detection of multiple tags even in low-SNR environments, achieving a peak-to-lobe ratio improvement from 11 dB to over 21 dB. This work marks a significant step toward scalable and reliable ambient backscatter localization systems in practical multi-tag environments.