# Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings
## 4 Simulation Results and Validation  
In order to verify the performance of the proposed clustering algorithms and the derivation of communication system performance, the RT simulation data were obtained based on the reconstructed 3D scenario of tower building which was completed with 3D design software SolidWorks and SketchUp at 1 GHz. As shown in Figure 1, the tower building has 11 floors with the height of 108.2 m. The TX antenna is placed on the edge of the tower building at the height of 5 m. 168 receiving antennas are uniformly placed at the heights of 3.5 m and 22 m, i.e., Floor 1 and Floor 4, and 132 receiving antennas are uniformly placed at the heights of 40 m and 58.5 m, i.e., Floor 7 and Floor 10, respectively. The electromagnetic simulation software used in this paper is Wireless Insite. The simulation parameters are listed in Table 2.  
Take the sensors at the center of above four floors as an example, the equivalent CIRs are obtained by using a different clustering algorithm and proposed cluster parameter calculation method based on the RT simulation data as shown in Figure 3. It can be seen from the figure that, with the increase height of receiving antenna, the number of rays and the received power would decrease. Moreover, it can be seen that the line-of sight (LoS) path exists when the receiver is located on the first floor, while LoS path disappears when the receiver is located on the high floor. It should be mentioned that it is hard to compare the clustering performance by CIRs directly, thus the calculated communication performance, i.e., BER or channel capacity can be used to indirectly evaluate the performance of different clustering algorithm. Take a sensor at the first floor as an example, QPSK modulation is used in the simulation, the BER curve of ray-based channel and the BER curves of cluster-based channel obtained by using three clustering algorithms are shown in Figure 4. According to (6) and (7), under the same SNR condition, the BER of cluster-based channel with improved k-means algorithm is smaller than that the ones of traditional k-means algorithm and sparsity algorithm. In addition, since different clustering algorithms are used to cluster rays received by receiver, cluster parameters, such as cluster delay and cluster power are different, and the theoretical BER derived is also different. As can be seen that the BER curve of the improved K-means algorithm is consistent with the simulated BER curve of RT algorithm, it can be considered that the clustering performance of improved K-means algorithm is better than other clustering algorithms. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Frequency & 1 GHz \\ Transmitting power & 20 dBm \\ Antenna type & Isotropic antenna \\ Polarization type & Vertical polarization \\ TX antenna location & 5 m \\ RX antenna location & 3.5 m, 22 m, 40 m, 58.5 m \\ Simulation material & Metal \\ Maximum number of reflections & 6 \\ Maximum number of diffractions & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation Parameters. The 3D BER curves at different positions of four different floor are shown in Figure 5. The transmitter is placed on the right side of the rocket, as shown in Figure 6. For the sensors on the first floor, it can be seen from Figure 5 that the LoS path exists at the right side of the sensors while disappears at the left side of sensors. Thus the BERs of sensors at the right side are better than the ones of left side. For the sensors on floors 4, 7, and 10, there is rarely LoS path. Therefore, the BERs of sensors at these floors are poorer than the one on the first floor. Since the sensors at the back of floor 10 are really far from the transmitter, the BER of which is much poorer. By studying the BER performance, the WSN can be placed in the position with low BER so as to optimize the layout of WSN inside the tower buildings. In addition, the communication performance of different sensors varies greatly.