Physiological Motion Sensing via Channel State Information in NextG Millimeter-Wave Communications Systems

Physiological Motion Sensing via Channel State Information in NextG Millimeter-Wave Communications Systems
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DOI:
10.1109/jmw.2022.3224375
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发表时间:
2023-01-01
影响因子:
--
通讯作者:
Boric-Lubecke, Olga
Boric-Lubecke, Olga
中科院分区:
其他
文献类型:
--
作者:
Ishmael, Khaldoon M.;Pan, Yanjun;Boric-Lubecke, Olga

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无线通信系统提供信道状态信息(CSI),可用于描述物理传播环境的特征。在该环境中人体的微小生理运动,例如与呼吸相关的运动,能够对CSI进行调制,从而实现无线生理传感,使通信系统能够检测和监测心肺运动。下一代毫米波通信系统由于波长小和方向性强的优势,为无线生理传感提供了更大的机遇。但是,由于大于波长的运动位移所导致的多径效应和相位混叠,也带来了挑战。这项工作引入了一个综合的数学CSI模型,以准确描述毫米波通信系统CSI的幅度和相位所捕捉到的生理运动。该模型能够解释复杂的CSI模式变化以避免混叠误差,并且已经通过机器人移动器进行的参数测量以及人体呼吸频率测量实验得到验证。在所有情况下,频率测量的误差都能稳定在10%以内,即0.02Hz,这表明了在下一代毫米波通信系统中整合生理传感的潜力。
Wireless communications systems provide channel state information (CSI), which can be used to characterize the physical propagation environment. The small physiological motion of human subjects in that environment, such as that associated with respiration, can modulate the CSI, thus allowing wireless physiological sensing through which a communications system detects and monitors cardiopulmonary motion. NextG millimeter-wave communications systems present even greater opportunities for wireless physiological sensing due to the advantages of small wavelength and high directionality. But challenges also arise due to the multipath effect and phase aliasing caused by larger-than-wavelength motion displacement. This work introduces a comprehensive mathematical CSI model to accurately characterize physiological motion captured by the amplitude and phase of the CSI of a millimeter-wave communications system. The model allows for the interpretation of intricate CSI pattern variations to avoid aliasing error and has been validated with experiments involving both parametric measures conducted with a robotic mover and respiration rate measurements for human subjects. In all cases, rate measurements could be consistently resolved within 10%, or 0.02 Hz, demonstrating the potential for incorporating physiological sensing in NextG millimeter-wave communications systems.