# A Novel Method to Determine the Optimal Location for a Cellular Tower by Using LiDAR Data
## 4 Results and Discussions
### Determination of the Strength of the Signal
#### 4.1.2 Terrain Parameter Determination  
Signal propagation of cell phone towers is analogous to a noise/sound propagation model. The determination of terrain parameters depends on signal transmission.  
Signal transmission pattern: Signals from cell phone towers suffer losses when traveling from one location to another, as proven by our own experiences. These losses are due to distance and barriers present between the cell phone tower and the cell phone user. While talking about attenuation losses in signal strength, there are some analogies between the losses in signal transmission and losses in sound transmission. They both have similar transmission patterns. They primarily travel directly from the source to the destination (in the case where there are no obstacles between them). When there is/are an obstacle(s) between them, it can also move indirectly by diffraction, reflection, and other means. The propagation path of the signal must be defined to determine the signal strength. The transmission path of the signal is calculated by evaluating the direct path or indirect path from the cell phone tower to the cell phone user location [2]. These paths (path over the top of building a barrier, path around the sides of the building, and path after reflection from ground and wall of a building) help to determine the parameters, such as distance and barrier attenuation. The transmission of the path is calculated by the path determination of the signal, as shown in Figure 11 below.  
Determination of signal strength equation: This step determines the equation for finding the signal strength at any location. The equation is fitted analogously to the semi-empirical formulae used in sound propagation modeling.  
\[\mathit{Sound\ level}(\mathit{Receiver})=\mathit{Sound\ level}(\mathit{ source})-\mathit{Distance\ attenuation}-\mathit{B\cdot A} \tag{1}\]  
\[\mathit{Distance\ Attenuation}=20\ log_{10}(D)+11 \tag{2}\]  
\[\mathit{B\cdot A}=5.65\ +66N+244N^{2}+287N^{3} \tag{3}\]  
\[\mathit{N}=\frac{\mathit{Path\ difference}}{\frac{\lambda}{2}} \tag{4}\]  
Figure 10: (**a**) Project Area of RGIPT campus, (**b**) Signal strength from nearest JIO cell phone tower at 1500 user locations on the RGIPT campus.  
\[\lambda=\frac{c}{f} \tag{5}\]  
\[Path\ Difference=D1-D \tag{6}\]  
where \(D=\) direct transmission path (m)  
\(D1=\) indirect transmission path (m)  
\(B\cdot A=\) barrier attenuation (dB)  
\(\lambda=\) wavelength (m)  
\(c=\) speed of light (m/s)  
\(f=\) frequency (Hz)  
\(N=\) Fresnel number  
For the RGIPT area, LIDAR point cloud data is generated [39], as shown in Figure S1a. From the LIDAR data, the digital elevation model is created, which is shown in Figure S2b. The LIDAR data and the DEM consist of the hostel area, academic building (AB1 and AB2), and teacher's housing of the RGIPT campus. Signal transmission paths were obtained from the information of building corners and edges estimated in [40]. This will determine the distance attenuation and barrier attenuation.  
Figure 11: Principal path of propagation explaining diffraction and reflection.