Abstract: With the rapid development of wireless communication technology,Wi-Fi has been widely used in public and private fields.Non-invasive breath detection technology based on wireless technology has a broad application prospect in the field of smart home.Considering that the existing solutions are difficult to explain the huge performance differences in different scenarios,this paper introduced the Fresnel edge diffraction model in the free space and designd a training free breathing detection sensing based on Wi-Fi signals.Firstly,we introduced the Fresnel Zone knife-edge diffraction model in free space,then verified the diffraction propagation characteristics of Wi-Fi signals in indoor environment.Se-condly,we accurately quantified the relationship between diffraction gain and micro thoracic displacement in human respiration,which Not only explains why Wi-Fi devices can be used to detect human breathing,but also demonstrates where is easier to detect.Finally,respiratory rate is estimated from RSS by fast Fourier transform (FFT).The algorithm in this paper can clearly know the distribution of good and bad positions of breath detection,and for good positions,the accuracy of breath estimation can reach 93.8%.Experiment results show that using a pair of transceivers makes centimeter-scale breathing perception possible and it is expected to provide a ubiquitous respiratory detection solution through a popular Wi-Fi infrastructure.

Key words: Fresnel zone, Human respiration sensing, Knife-edge diffraction model, Training-free, Wi-Fi signals