发表机构
KU Leuven; Interuniversity Microelectronics Centre (IMEC)（荷语鲁汶大学; 微电子技术研究中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文通过Blender建模和Sionna光线追踪仿真，验证了FR3频段蜂窝通信在室内监测呼吸和心跳的可行性，并与FR1和FR2频段对比ISAC性能，展示了其跨频段应用价值。
AI 中文摘要
生命体征感知得益于无线通信的演进，但其本身具有挑战性，因为胸部的微多普勒特征可能受到多径、身体运动和噪声的干扰。此外，频率范围（FR）3频段（覆盖7-24 GHz）的前景十分诱人，因为厘米级波长提高了对胸部运动的相位灵敏度，而其丰富的带宽和丰富的多径增强了时间和空间分集。在本文中，我们验证了在室内环境中使用FR3频段蜂窝通信监测人体呼吸和心跳的可行性。我们使用Blender对生理上准确的生命体征信号进行建模作为真实值，并利用Sionna光线追踪仿真，发现在FR3频率下提取呼吸和心跳波形是可行的。此外，我们针对代表性的sub-6 GHz（FR1）和毫米波（FR2）频率进行了ISAC性能对比分析，表明了该研究跨频段的实用性。
英文摘要
Vital Signs Sensing, enabled by the evolution of wireless communications, is inherently challenging as the chest's micro-Doppler signatures can be corrupted by multipath, body movement and noise. Additionally, the prospects of the Frequency Range (FR) 3 band, spanning 7-24 GHz, are compelling due to centimeter-scale wavelength improving phase sensitivity to chest motion, while its abundant bandwidth and rich multipath enhance temporal and spatial diversity. In this paper, we validate the feasibility of using cellular communications in the FR3 band to monitor a human's breathing and heartbeat in an indoor environment. Using Blender to model physiologically accurate vital-signs signals as ground truth and Sionna Ray Tracing simulations, we find that it is feasible to extract breathing and heartbeat waveforms at FR3 frequencies. Furthermore, we perform a comparative analysis of ISAC performance against representative sub-6 GHz (FR1) and mmWave (FR2) frequencies, indicating the utility of the study across the frequency bands.
