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Poster Abstract: Obstruction-Free Physiological Motion Sensing in NextG Networks with Intelligent Reflective Surfaces

Denny Landika,Saige Dacuycuy,Yao Zheng

IoTDI '23: Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation(2023)

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Abstract
This poster abstract shows the possibilities of incorporating an Intelligent Reflective Surface (IRS) that operates at the 3.5 GHz band in order to enhance signal coverage and perform obstruction-free physiological motion sensing. At an operating frequency of 3.5 GHz, the IRS redirects an incoming signal at normal incidence to 34.. A testbed is developed that allows us to test the quality of periodic motion (i.e. simulate breathing). The transmit horn is pointed at a metallic target that is oscillating at 0.2 Hz, where the target scatters the transmitted signal. The scattered signal will reach the IRS, which then redirects the signal to the receive horn. The setup was tested for three possible cases, with an IRS, a copper plate, and an absorber as the target. The merits of implementing an IRS in physiological sensing are discussed and evaluated.
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Key words
Physiological Sensing,Intelligent Reflective Surface,NextG networks
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