# A Novel Dynamic Transmission Power of Cluster Heads Based Clustering Scheme
## 5 Performance Evaluation
### Analysis of DTPCH-C Clustering Scheme  
Firstly, the optimal grid division density is determined. If the grid division is very sparse, some cluster members can receive data packets from the cluster head without a lot of transmitting power. In this case, the energy is wasted because much transmitting power is set by the grid. However, when the grid division is dense, the transmitting power of CHs is frequently changed, which results in energy consumption. Figure 6 shows three ways to divide the grid. \(M\) represents the number of discrete transmission power levels of the CH (in different colors). \(M=4\), \(M=7\) and \(M=10\) indicate that the transmission power of the CH is divided into four levels, seven levels and ten levels, respectively. Through the simulation, the scheme with the longest CH survival time can be obtained, which will be applied for the subsequent experimental tests. To accurately find the optimal partition scheme, we conducted two groups of experiments.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Network area & 2000 m \(\times\) 2000 m \\ UAV maximum transmission power & 0.3 mW \\ UAV reception sensitivity & 0.3 nW \\ Intra-cluster carrier frequency & 2.4 GHz \\ Inter-cluster carrier frequency & 5 GHz \\ Number of UAVs & 20–120 \\ Speed of UAVs & 40 m/s \\ Transmission range & 500 m \\ Mobility model & Gauss-Markov \\ Initial energy of a node & 10 J \\ Traffic type & CBR \\ CBR rate & 2 Mbps \\ HELLO message interval & 2 s \\ Data packet interval & 1 s \\ Data packet size & 4000 bit \\ Control packet size & 100 bit \\ UAV reception sensitivity & \(-95\) dBm \\ Number of runs & 1500 \\ Consumption of adjusting transmission power & 0.1 m) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Simulation parameters.  
Figure 6: Three different methods of dividing grid.  
Figure 7 shows the survival time of FANET versus the number of UAVs under different grid partitioning conditions. We can observed that the lifetime of FANET based on the clustering scheme decreases as the number of UAV increases. This is because the mobility and the stability of FANET become dramatic when the number of UAVs increases, resulting in a reduction in the lifetime of FANET.  
Figure 8 shows the lifetime of FANET versus the number of UAVs under different grid partitioning conditions. We observed that when the number of grids is small at the beginning, with the increased number of grids, the lifetime of the network increases; when the grid partition range is increased to seven intervals, the FANET survives the longest time. After that, the lifetime of the network decreases as the number of intervals increases. This is because when the division of the communication range is small, the division scope of the transmission power settings is also small, the effect of saving energy is not obvious. However, when the grid division is very dense, CHs need to switch transmission power frequently, which also causes energy loss. As shown in Figure 8, the optimal value is \(M=7\) in this simulation environment. We will conduct subsequent comparative tests with \(M=7\) which indicates that the transmission power of the CH is divided into seven levels.  
The specific transmission power settings of the optimal scheme are listed in Table 5. To improve the success rate of information transmission, we adjusted each value appropriately.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Grid** & **P/mW** \\ \hline Purple & 0.015 mW \\ Dark blue & 0.035 mW \\ Light blue & 0.065 mW \\ Green & 0.1 mW \\ Yellow & 0.15 mW \\ Orange & 0.2 mW \\ Red & 0.3 mW \\ \hline \hline \end{tabular}
\end{table}
Table 5: Specific transmission power settings.  
Figure 7: Lifetime of FANET in different grid partitioning conditions versus the number of UAV nodes.