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Doppler radar node occupancy sensors are promising for applications in smart buildings due to their simple circuits and price advantage compared to quadrature radar sensors. However, single-channel sensitivity limitations may result in low sensitivity and misinterpreted motion rates if the detected subject is at or close to “null” points. We designed and tested a novel method to eliminate such limits, demonstrating that passive nodes can be used to detect a sedentary person regardless of position. This method is based on characteristics of chest motion due to respiration, found via both simulations and experiments based on a sinusoidal model and a more realistic model of cardiorespiratory motion. In addition, respiratory rate variability is considered to distinguish a true human presence from a mechanical target. Sensor node data were collected simultaneously with an infrared camera system, which provided a respiration signal reference, to test the algorithm with 19 human subjects and a mechanical target. The results indicate that a human presence was detected with 100% accuracy and successfully differentiated from a mechanical target in a controlled environment. The developed method can greatly improve the occupancy detection accuracy of single-channel radar-based occupancy sensors and facilitate their adoption in smart building applications. 

A 28-GHz multibeam joint communication and sensing system called SideSense is presented, in which a line-of-sight (LoS) beam is used to maintain reliable communication, while other sensing beams are used to enhance physiological motion detection. SideSense decodes the motion frequency and shape from the channel state information (CSI) by first tuning the gain ratio and phase differences between the LoS communication beam and non-LoS (NLoS) beam to maximize the sensing signal-to-noise ratio (SSNR) without significantly degrading the communication channel capacity (CCC). Analytical results based on a bistatic model are presented to show a gain ratio of around 1 and a phase difference of 90° or 270°, which are ideal for optimizing both SSNR and CCC. Experiments based on an array of phased array (APA) beamformers and orthogonal frequency-division multiplexing (OFDM) waveforms with phantom and human subjects are presented to validate the performance of SideSense. Results show that SideSense can improve SSNR by 84% while reducing CCC by 35%, an acceptable decrease within the normal operational parameters of a millimeter-wave (mmWave) communication system, which would not trigger a link reestablishment procedure, e.g., communication beam realignment.