Abstract
A novel dynamic channel model for on-body wireless communication during walking is proposed. The developed model utilizes a human walking model which provides detailed information on the movement of the human body parts. The diffraction of the signal around the body parts is used to describe the time-varying shadowing effects. Body part movements are also used to estimate the signal fading caused by angular variations of the transmitting and receiving antenna gains. A Rice distribution is used to represent the multipath fading effects caused by objects around the human body. Simulation results of the first- and second-order statistics of the received signal affected by moving body parts for 2.4 GHz signal are presented. To illustrate the capabilities of the developed model, time series were generated and used in system performance calculations. The obtained results give an insight into the potential advantages of link diversity technique in wireless body area networks (WBANs).
Highlights
In recent years, body area networks are gaining increasing attention because of their potential applications in various domains such as health, entertainment, and sports
The use of wireless communication in the immediate vicinity of the human body eliminates the need for wired interconnections and the concept of wireless body area network (WBAN)
The movements of the body parts are used to estimate the signal fading caused by angular variations of the antenna gains
Summary
Body area networks are gaining increasing attention because of their potential applications in various domains such as health, entertainment, and sports. They are synchronized with the left human body motion, and the origin is at the left heel strike. The trajectories of flexing for the elbow, hip, knee, ankle, and thorax are modeled using cubic spline passing through control points (for a given relative velocity) located at the extremities of the trajectories. Variations of the right human body parts are obtained by a phase displacement of half a cycle In the following, these time-dependent body part translations and rotations are used to characterize the time-varying on-body wireless channel during walking
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