# Research on Networking Protocols for Large-Scale Mobile Ultraviolet Communication Networks
## 4 Simulations
### Channel Conditions  
The performance of UV communication networks is dependent on the performance of UV point-to-point communication systems. Factors such as atmospheric turbulence and background noise affect these systems, which are ultimately reflected in communication coverage, data rate, and BER. In current research, due to significant path loss during atmospheric propagation of UV light, the communication rate at hundred-meter distances typically ranges from 100 Kbps to 10 Mbps. In this section, the basic simulation conditions are set as follows: communication coverage of 100 m, point-to-point data rate of 10 Mbps, and BER of \(10^{-6}\). However, as channel conditions such as atmospheric turbulence change, the performance of the communication system may improve or deteriorate, manifested as reduced communication range, increased BER, etc.  
By setting parameters such as different communication coverage and BER, the network performance under varying channel conditions can be simulated. Figure 6 simulates the network performance when \(n\) is 100, \(\rho\) is 0.00012, the link rate is 10 Mbps, and \(\lambda\) is 0.7, as the node communication distance gradually extends from 60 m to 150 m with changing channel conditions. The results show that as the communication distance increases, the network throughput exhibits a trend of first increasing and then decreasing. This is because when the communication distance is short and the network density is low, the network is highly likely to be partitioned into multiple independent subnets or isolated nodes. In this case, the actual transmittable data of nodes is significantly reduced, a phenomenon that improves as channel conditions improve and node communication distance increases. However, when network density remains constant, further increasing the node communication distance leads to a further decline in total network throughput. This is because, as the node communication distance increases, the number of one-hop neighbors for each node also increases. Consequently, whenever a transmission path is successfully established, more nodes enter the silent state, which reduces the number of simultaneously established transmission paths in the network.  
\begin{table}
\begin{tabular}{c c c} \hline
**Parameter** & **Value** & **Meaning** \\ \hline Communication coverage & 100 m & The maximum communication distance from point to point \\ \(T_{\text{data}}\) & 25 ms & The time of each data transmission time slot \\ Link rate & 10 Mbps & The maximum communication rate from point to point \\ Simulation time & 3000 s & The duration of the simulation \\ BER & \(10^{-6}\) & Bit error rate \\ \(n\) & 100 & Number of nodes \\ \(A\) & - & Area of the distribution region \\ \(\rho\) & - & Node density, \(\rho=n/A\) \\ \(\lambda\) & - & At each node, the arrival of data follows a \\  & & Poisson distribution with intensity \(\lambda\). \\ \(T_{\text{trans}}\) & - & The time required for a complete \\ \(T_{\text{ref}}\) & - & \(\text{Network connection matrix update period}\) \\ \(v\) & - & The moving speed of nodes, in meters per second (mps) \\ \hline \end{tabular}
\end{table}
Table 2: Basic parameters in the simulation.  
Additionally, Figure 6 demonstrates that network throughput decreases significantly when channel conditions deteriorate and BER increases. This occurs because a higher BER not only leads to data frame transmission failures but, more critically, elevates the probability of nodes constructing incorrect connection matrices. Once a node establishes an erroneous connection matrix, it may trigger a cascade of transmission failures for multiple paths until the next neighbor discovery cycle.  
Thus, in practical implementations, adjusting parameter settings according to specific application scenarios is imperative. Under favorable channel conditions, nodes can be deployed across a broader operational space; when channel conditions degrade, the network should reduce deployment span and increase node density to ensure optimal performance.