Motion Detection over 5G through Sensing Signal Disturbance Analysis leveraging COTS platform
Ioannis Tsilikis, Evanthia Faliagka, Michael Paraskevas, Vaggelis Kapoulas, Christos Antonopoulos, Nikolaos S. Voros · 2025
This study presents a system-level investigation aimed at reliably detecting human movement in indoor environments using antenna signal quality indicators derived from a commercial off-the-shelf (COTS) private 5 G mobile network deployment. The equipment utilized is capable of emulating a fully integrated telecommunications system, supporting the Integrated Sensing and Communication (ISAC) standard. The primary objective is to evaluate whether common measurements such as Channel Quality Indicator (CQI), Modulation and Coding Scheme (MCS), and Signal-to-Noise Ratio (SNR) can effectively indicate human presence and movement. Experimental results demonstrated that human motion events within the line-of-sight (LOS) path resulted in measurable and repeatable signal degradation. Specifically, SNR values were found to decrease by up to 31.9%, while in more pronounced cases, reductions exceeding 41.5% were recorded. Simultaneously, downlink MCS values dropped sharply from index 10-12 (corresponding to 16-QAM modulation with moderate coding rates), dropped sharply to near zero, as the system adapted in real time to the deteriorating channel conditions. A strong positive correlation between signal degradation and link adaptation was confirmed, with a Pearson correlation coefficient of approximately $\mathbf{r}=\mathbf{0. 9 2}$ observed between SNR and MCS. Furthermore, a correlation of $\mathbf{r}=0.84$ was recorded between SNR and CQI. During the evaluation, SNR, CQI, and MCS measurements provided the most significant variations associated with human movement scenarios, particularly when the LOS was obstructed.