Michal Mackowiak

An Off-Body Channel Model for Body Area Networks in Indoor Environments

This paper presents an off-body channel model for body area networks (BANs) in indoor environments. The proposed model, which is based on both simulations and measurements in a realistic environment, consists of three components: mean path loss, body shadowing, and multipath fading. Seven scenarios in a realistic indoor office environment containing typical scatterers have been measured: five were static (three standing and two sitting) and two dynamic (walk in a fixed place and real walk). The measurement equipment and measurement procedures are described. The mean path loss component is modeled as a log function of distance, the path loss exponent being in the range between 0.4 and 1.6, while a statistical perspective is taken for the other two components, i.e., body shadowing is found to be well modeled by a log normal distribution and multipath fading by Rice or Nakagami-m distributions, depending on body motion characteristics. The correlation between the selected distributions and empirical data is not lower than 0.95, typically being greater than 0.98. The novelty of this model is that it takes the statistical influence of various parameters and features present in BANs into account, such as body influence, placement of the wearable antennas, user orientation in the environment, dynamism of the BAN scenario, and propagation conditions.

A statistical analysis of the influence of the human body on the radiation pattern of wearable antennas

This paper introduces a statistical approach for modelling antennas behaviour in the vicinity of the human body. The statistics of radiation patterns, i.e., average and standard deviation, have been calculated for Uniform and Rayleigh antenna to body distance distributions. The coupling between the body and the antenna and reduction of antenna efficiency leads to the distortion of the antenna radiation pattern, which depends on the distance as well as on the location on the body. A patch antenna operating at 2.45 GHz was simulated in CST, near to regions of a voxel human model, i.e., Head, Chest, Arm and Leg. Results show that the relative change of the average radiation pattern for an antenna located on the Chest can reach 24%.

Modelling on- and off-body channels in Body Area Networks

This paper presents an analysis of the capacity of a 2×2 MIMO system in on- and off-body communications in an indoor multipath environment. The modelling of wearable antennas in Body Area Networks (BANs) has been separated into antennas in the vicinity of the body (full wave simulations), including body dynamics (taken from motion capture analysis), and the environment (clusters of scatterers). A Geometrically Based Statistical Channel model adapted to the BANs environment is used. Based on proper metrics, optimum 2×2 antenna placements are suggested. The best performance is obtained when the on-body sink is on the front and back of the body, and data sensors are on the head, with a capacity gain of 0.97. This sink configuration also enables a good connectivity with an external base station (the capacity gain reaches 0.83).

Measurements of path loss in off-body channels in indoor environments

The main goal of the paper is to investigate the influence of body orientation and on-body antenna placement on the path loss in off-body communications. In addition, the influence of different bodies is analysed.

Comparing off-body dynamic channel model with real-time measurements

This paper presents a novel approach for modelling the influence of body dynamics on the radiation pattern of wearable antennas in Body Area Networks (BANs), particularly in off-body radio channels. The modelling of wearable antennas in BANs has been separated into antennas in the vicinity of the body (full wave simulations), including body dynamics (motion capture), and an indoor environment (clusters of scatterers). An anechoic and indoor scenarios are simulated, for a walking body, and for 3 on-body antenna placements (i.e., Arm, Head and Torso). The comparison of a path loss between simulated results and real-time measurements shows a good agreement, with an average difference of 4.5 dB (standard deviation of 0.1 dB) for the example case of the node on the Head, in an indoor environment.

A statistical approach to model antenna radiation patterns in off-body radio channels

The goal of this paper is to introduce a statistical approach for modelling antennas behaviour in the vicinity of the human body. A very preliminary model based on geometrical optics has been developed, and calculations have been performed for parallel and perpendicular polarisations, for 0.915, 2.45 and 5.8 GHz, for various human body tissues, and for several antenna locations on the body. The statistics of radiation patterns, i.e., average, minimum, maximum and standard deviation, have been calculated for Uniform and Rayleigh antenna to body distance distributions. The results show a much higher variation of changes among various frequencies of average radiation patterns for the Rayleigh distribution, which can reach 60%, while for the Uniform one, it can go up to 30%. When modelling various tissues, the results show that the average radiation pattern is changing no more than 15%, but the change of standard deviation can reach 70%.

Statistical path loss model for dynamic off-body channels

This paper presents a statistical model for off-body radio channels in an indoor multipath environment. The model considers the distance dependent mean path loss, and describes body shadowing and fast fading components in a statistical way. The modelling of wearable antennas in Body Area Networks (BANs) has been separated into antennas in the vicinity of the body (full wave simulations), including body dynamics (taken from motion capture analysis), and the multipath environment (clusters of scatterers). A Geometrically Based Statistical Channel model adapted to the body environment is used. Several body postures and orientations, and 8 different antenna placements, are analysed for a BAN operating in 2.45 GHz. The body shadowing component is described by an average standard deviation equal to 4.6 dB, being 0.9 dB higher than the fast fading one.

Correlation analysis of off-body radio channels in a street environment

This paper presents an analysis of the correlation between various links in off-body communications in a multipath environment. The modelling of wearable antennas in Body Area Networks has been separated into antennas in the vicinity of the body (full wave simulations), including body dynamics (taken from motion capture analysis), and street environment (clusters of scatterers). Multi-Path Components are calculated using a Geometrically Based Statistical Channel model. A street scenario is simulated, for a running or walking body, and for 9 on-body antenna placements. The results allow to identify 3 classes of antennas, i.e., co-directed (CD), cross-directed (XD) and opposite-directed (OD). The CD class is characterised by the highest average correlation, equal to 0.56, whereas XD and OD present values of 0.40 and 0.28, respectively.

A comparison of phantom models for on-body communications

Full wave simulations with realistic models of the human body are a powerful tool to study Body Area Networks. Usually, some simplifications are introduced in simulation models to speed up computation routines, and to save memory resources. This paper analyses the use of truncated voxel models, and discusses the option of using homogeneous or voxel phantoms. The metric used for the assessment is the performance of a patch antenna placed near the body (human or phantom). The statistical behaviour of the patch radiation pattern (over distance to the body) is compared via measurements and simulations. A pattern average difference of 0.9 dB is found, in the area of interest for on-body communications. The performance of the patch when using homogeneous or voxel models is very similar (12% difference), and a reduction of 5 times in the simulation time is obtained when using homogeneous models.

Modelling dynamic body-to-body channels in outdoor environments

Wireless Body Area Networks (BANs) refer to body centric wireless communications, [1], [2], where one or more of the communication devices are attached to the human body. When communications take place between wearable devices on two independently moving bodies, the body-to-body channel is considered, [3]. In this case, the antennas on both sides of the radio link are influenced by the presence of the body. The goal of this paper is to address the development of a flexible method to model radio channels in body-to-body communications. The model can be applied to any type of antenna, however, the radiation pattern of the antenna has to be previously modelled on the static body (e.g., voxel model) using full wave simulations, [4]. This ensures that the coupling of the body, which has an impact on the radiation pattern of antenna, is included. As the proposed model for body dynamics is based on motion capture analysis, [5], any type of body movement can be considered (e.g., run). The environment consists of clusters of scatterers, and the Geometrically Based Statistical Channel model adapted to the BANs is used, [6], to calculate Multi-Path Components (MPCs). The practical scenario of 2 bodies running in a street in an urban area (i.e., micro-cell) has been taken as a study case, Fig. 1. A patch antenna, [7], operating in the 2.45 GHz Industrial, Scientific, and Medical (ISM) band is used. There are several typical placements of antennas in BANs, the following locations on both bodies being analysed: TO F and TO B (front and back side of the Chest); WA F (front side of the Waist); HE F, HE B, HE L and HE R (front, back, left and right side of the Head); AB L and AB R (left and right side of the Arm). This results in 81 possible body-to-body links. In order to model the street environment, a set of 10 clusters, of 3 scatterers each, has a uniform distribution in the half space of an ellipsoid. Two bodies are running in parallel on a straight line, in the middle of the street, with a 2 m separation between body centres. The running speed was set to 14.4 km/h. In order to obtain statistical parameters, each dynamic scenario has been repeated 30 times (for a random distribution of scatterers).