Abstract
This paper is about designing a 3D no n-stationary wideband indoor channel model for radio-frequency sensing. The proposed channel model allows for simulating the time-variant (TV) characteristics of the received signal of indoor channel in the presence of a moving object. The moving object is modelled by a point scatterer which travels along a trajectory. The trajectory is described by the object’s TV speed, TV horizontal angle of motion, and TV vertical angle of motion. An expression of the TV Doppler frequency caused by the moving scatterer is derived. Furthermore, an expression of the TV complex channel transfer function (CTF) of the received signal is provided, which accounts for the influence of a moving object and fixed objects, such as walls, ceiling, and furniture. An approximate analytical solution of the spectrogram of the CTF is derived. The proposed channel model is confirmed by measurements obtained from a pendulum experiment. In the pendulum experiment, the trajectory of the pendulum has been measured by using an inertial-measurement unit (IMU) and simultaneously collecting CSI data. For validation, we have compared the spectrogram of the proposed channel model fed with IMU data with the spectrogram characteristics of the measured CSI data. The proposed channel model paves the way towards designing simulation-based activity recognition systems.
Highlights
In wireless communications, the compound Doppler effect caused by the moving objects or bodies opened up opportunities for many applications
We proposed a no n-stationary wideband channel model and its TV Doppler power characteristics when there is a moving object in the 3D space
We derived the TV Doppler shift caused by the moving object in terms of the TV speed, azimuth angles of motion (AAOM), elevation angle of motion (EAOM), azimuth angle of departure (AAOD), elevation angle of departure (EAOD), AAOA, and elevation angle of arrival (EAOA)
Summary
The compound Doppler effect caused by the moving objects or bodies opened up opportunities for many applications These applications track the scattered wave components by the moving bodies for drone detection [1], gesture recognition [2], human gait assessment for diagnosis and rehabilitation [3], and tracking human activities using no n-wearable radio-frequency-based (RF-based) elder-care [4]. In order to design such a realistic channel model with Doppler power characteristics close to experimental data, the TV trajectory of a moving object plays an important role as the Doppler shift depends on the TV speed, AAOM, EAOM, EAOD, AAOD, EAOA, and AAOA.
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