# Analysis of Human Body Shadowing Effect on Wireless Sensor Networks Operating in the 2.4 GHz Band
## 3 Results
### Analysis of Human Body Shadowing in an Indoor Environment Using XGtd(tm)  
The XGtd(tm) program is suitable for simulating the interaction of electromagnetic waves with large objects. It was therefore used to analyze the body shadowing effect in a wireless sensor network located in a typical hospital room. The multiple reflections from the walls in such a propagation environment made the path loss difficult to predict [42]. For this reason, computer models of path loss in indoor environments are particularly important for designers of wireless sensor networks. The geometry of the indoor scenario for simulating the effect of shadowing is presented in Figure 9. The room is 9 m long and 5.4 m wide, and the ceiling height is 3.5 m. The walls, floor, and ceiling were modeled as being made of 35 cm thick concrete. The material properties of the concrete were taken from the material library available in XGtd(tm). The electric permittivity was equal to \(\varepsilon_{r}=15\) and the conductivity was \(\sigma=0.015\) S/m. The transmitting dipole antenna that modeled the transmitting sensor was located in the middle of the room, 1.3 m above the floor. The receiving dipole antenna (of the receiving sensor) was placed at the same height, but its position was changed by approximately 1 m, from 2.5 m from the transmitting antenna to 3.5 m.  
Figure 8: Ray-paths for human body models with six sidewalls: (**a**) For the receiver located at the distance, \(b=1\) m; (**b**) For the receiver located at the distance, \(b=1.1\) m.  
The simulations were performed for a case with no human body located in the room and in the case of human bodies placed between the transmitting and receiving antennas. As shown in Figure 9, for the body shadowing case, three configurations were considered: One person placed in position \"A\", two people in positions \"A\" and \"B\", and three people in positions \"A\", \"B\", and \"C\". The model with six side walls was used to simulate the human body. Figure 10 presents the results of the path loss simulations in XGtdTM for the indoor scenario. Due to the multiple reflections from the walls, the path loss changes dynamically with changes in the position of the receiving antenna and the short-term fading is visible here. To compare the results obtained with and without the presence of human body models, the median path loss was calculated for displacements of the receiving antenna across a distance of 1 m. In the case of no human body between the antennas, the median path loss was 45 dB, the minimum value was 41 dB, and the maximum value was 55 dB. In the case of one person in position \"A\", the median path loss increased to 54.5 dB, the minimum value was 46 dB, and the maximum value was 61 dB. For two people (in positions \"A\" and \"B\"), the median path loss was 55 dB, the minimum value was 49 dB, and the maximum value was 69 dB. For three people (in positions \"A\", \"B\", and \"C\"), the median path loss was 56 dB, the minimum value was 50 dB, and the maximum value was 79 dB. These results show the additional path loss that has to be included in the link budget analysis of wireless sensor networks operating inside buildings. Figure 10: Results of path loss simulation for the indoor scenario in XGtdTM. Figure 9: Geometry of the indoor scenario for simulating the shadowing effect in XGtdTM (picture not to scale). The simulations were performed also for the second geometrical scenario, with human bodies placed around the transmitting antenna. As shown in Figure 11, for the body shadowing case, three spatial configurations were considered: Two persons placed in position \"D\" and \"E\", three people in positions \"A\", \"D\", and \"E\", and four people in positions \"A\", \"D\", \"E\", and \"F\". Apart from the location of people, all the geometrical parameters of the experiment were preserved from the previous case, as illustrated in Figure 9.  
In Figure 12, the results of path loss simulations obtained for the second scenario are presented.