User Localization using RF Sensing: A Performance comparison between LIS and mmWave Radars
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Abstract (arXiv)
Since electromagnetic signals are omnipresent, Radio Frequency (RF)-sensing has the potential to become a universal sensing mechanism with applications in localization, smart-home, retail, gesture recognition, intrusion detection, etc. Two emerging technologies in RF-sensing, namely sensing through Large Intelligent Surfaces (LISs) and mmWave Frequency-Modulated Continuous-Wave (FMCW) radars, have been successfully applied to a wide range of applications. In this work, we compare LIS and mmWave radars for localization in real-world and simulated environments. In our experiments, the mmWave radar achieves 0.71 Intersection Over Union (IOU) and 3cm error for bounding boxes, while LIS has 0.56 IOU and 10cm distance error. Although the radar outperforms the LIS in terms of accuracy, LIS features additional applications in communication in addition to sensing scenarios.
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7 of 19 references.
References · 7
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- 2019Fast Graph Representation Learning with PyTorch Geometriccited by 2,414
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- 2021Tesla-Rapture: A Lightweight Gesture Recognition System from mmWave Radar Point Cloudscited by 10
- 2020Assessing Wireless Sensing Potential with Large Intelligent Surfacescited by 2
- 2021Radio Sensing with Large Intelligent Surface for 6Gcited by 2
- 2021Integrating Sensing and Communication in Cellular Networks via NR Sidelinkcited by 1
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