# Analysis of Human Body Shadowing Effect on Wireless Sensor Networks Operating in the 2.4 GHz Band
## 2 Materials and Methods
### Human Body Model for Shadowing Analysis in UTD-Based Program
In [13], the authors considered different elementary objects, such as a rectangular blade, a parallelepiped, or a circular cylinder, for modeling the human body. With such a simplistic approach, it was found that it was possible to estimate only the mean attenuation introduced by the body, averaged over different positions of a person relative to the transmitting antenna. It was not possible to identify the shadow region in the proximity of the human body, which is important for designers of wireless sensor networks utilizing wireless nodes located close to people in buildings. Cylinder-based models of the human body presented in the literature [39; 40; 41] show that this geometrical figure is adequate for both simulations and measurements of the interactions between a human body and electromagnetic waves. In previous work by the author [25], a dielectric cylinder-based model of the human body was successfully applied in the XGtd(tm) program to simulate the body-shadowing effect in the 3.6 GHz band. It was necessary to further simplify the original circular cylinders by using polygonal prisms. The number of side walls used to approximate the body cylinder was found to be frequency dependent and had a major influence on the results of body shadowing simulations elaborated in the XGtd(tm) program. The cylindrical model of the human body approximated with polygonal prisms developed and applied previously by the author to study the body-shadowing effect in the 3.6 GHz band was used as the basis for designing a body model suitable for simulating body shadowing in XGtd for the 2.4 GHz band. The number of sidewalls used for cylinder approximation was optimized to obtain the best correspondence between the body shadowing simulations and the results of FDTD. The human body model was simplified using 2 polygonal prisms, as shown in Figure 5. The dimensions were as follows: \(D_{1}=310\) mm, \(D_{2}=110\) mm, \(H_{1}=1800\) mm, \(H_{2}=530\) mm, \(L=200\) mm. The material used to model the human body had the same properties as the human body model proposed by the author to study the body-shadowing effect in the 3.6 GHz band [25]. Its relative electric permittivity was \(\varepsilon=52\), and its specific conductance was \(\sigma=1.8\) S/m. Those values of material parameters were also successfully used by the author for simplified numerical models of the human body in the FDTD method [40; 41]. The simulations were performed in a free space environment, assuming that the only obstacle between the dipole antennas was the human body model. Figure 6 presents the results of path loss simulations in XGtd(tm) with different numbers of prism sidewalls used to approximate the main cylinder. The influence of the number of sidewalls used to model the arm cylinders was negligible. In further analysis, only the number of sidewalls in the main prism was considered, while the number of sidewalls approximating the arms was adjusted to match the number of walls in the main prism. The results were compared to the path loss simulated in XFdtd. The distance of the transmitting dipole from the body axis (_a_) was assumed to be equal to 2 m. The reference result obtained in XFdtd(tm) was calculated for the same spatial configuration. The differences between the path losses obtained with XGtd(tm) and XFdtd(tm) depended on both (1) the number of sidewalls approximating the main body cylinder, and (2) the distance (_b_) between the receiving antenna and the human body. To find the best model configuration, the median values for the path loss across three distance ranges were compared. Figure 5: Geometry of the simplified human body model in the XGtd(tm) program: (**a**) Top view; (**b**) Front view. Table 1 presents the differences between the median values for path loss obtained with the FDTD and UTD methods.