Time-varying on-body wireless channel model during walking
Michael Cheffena
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Gjvik University College
, Teknologivn. 22, Gjvik N-2815,
Norway
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).
1 Introduction
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 hence the concept of wireless body area
network (WBAN).
However, various propagation measurement results
have shown that the on-body wireless channel is
subject to fading caused by the movement of the human
body [1-9]. In addition to the shadowing of the signal
by moving body components, signal reflection/scattering
from objects around the human body result in multipath
fading effects [1,2,10]. Furthermore, the angular
variations of the antenna gains during walking give rise to
time-varying channel conditions [9,11,12]. Understanding
the on-body propagation channel is thus important for
successful design of WBAN systems.
A number of studies on the signal fading caused by
the movement of the human body are reported in the
literature, most of them are based on radio frequency
(RF) measurements [1-9] or using numerical simulations
such as finite-difference time-domain (FDTD) [10,13-15].
A finite-state Markov model for dynamic on-body
channels, where the model parameters are extracted from the
RF measurements is reported in [5]. A two-state
alternating Weibull renewal process for describing the dynamical
properties of the on-body channel is proposed in [6].
In addition, by modeling the trunk, arms, and legs of a
human body as infinite cylinders, Liu et al. [7] proposed
a method for calculating the scattering signal by body
components. A series of time-consecutive scenarios with
different positions of the arms at the azimuth is included
to describe the time-varying behavior of the channel. In
[15], a phantom created by an animation software is used
for simulating the time-varying on-body communication
channel. Similar study is conducted in [16] to characterize
the shadowing properties of an arm-waving human body.
In this paper, a novel dynamic channel model for
onbody wireless communication during walking is proposed
by utilizing a human walking model. Using geometrical
relations, the diffraction of the signal around body parts is
calculated to describe the time-varying shadowing effects.
The movements of the body parts are also used to
estimate the signal fading caused by angular variations of the
antenna gains. In addition, a Rice distribution is used to
represent the multipath fading effects caused by objects
around the human body. To show the potential of the
proposed model, time series were generated and used
in system performance calculations. The results give an
insight into the advantages of link diversity technique in
WBANs.
The paper begins by discussing the human walking
model in Section 2. The proposed dynamic channel
model for on-body wireless communication is presented
in Section 3. Numerical results and discussions are
given in Section 4. Finally, the conclusions are given in
Section 5.
2 The human model
Human walking models have been developed for use
in, e.g., virtual reality [17-19]. Such models may
provide detailed informations on the movement of human
body parts which are necessary in characterizing the
time-varying on-body wireless channel. Figure 1 shows a
human body model consisting of 12 body parts which are
modeled as cylinders except the head which is modeled
as a sphere. The body parts are connected to each other
by translations and rotations (see Table 1 for description)
and flex as the person walks. These time-dependent body
part translations and rotations have to be known in
order to characterize the time-varying on-body wireless
channel.
Figure 1 Human body model with translations and rotations
(see Table 1) [19,20].
Based on experimental data, Boulic et al. [19] developed
a model for calculating the tim (...truncated)