# An Aquatic Mobile Sensing USV Swarm with a Link Quality-Based Delay Tolerant Network
## 5 Link Quality Characterization for Simulation Support  
Based on ROS and Gazebo, a realistic simulation environment was developed to facilitate the evaluation of new routing and navigation strategies in controlled aquatic scenarios. This application is able to simulate a realistic aquatic environment with respect to the aquatic sensors on each USV and also the kinodynamics of the motion planning. The simulator uses the same modules of an USV in a real environment, and simulates all the hardware as represented in Figure 7. With respect to the network layer, an additional Network Module was created to have a behavior as the one observed in real wireless networks when applied to aquatic environments. To characterize the link quality of an aquatic wireless network to be considered in the Network Module, values of SSI and Achievable Throughput (At) are obtained through experiments in real aquatic scenarios for several aquatic environments. Two distinct scenarios are considered: the AlgaPlus, characterized by tanks influenced by tides and wind, which led to turbulent waters, and where aquaculture is carried out; and the Water Biological Treatment Plant (WBTP) of the University of Aveiro, characterized by standing water, sheltered wind tanks, and has a lot more suspend particlesthan the other, which leads to reduced visibility. To obtain the aforementioned network metrics, two USVs are used, one mobile and one static. Both water tanks' USV positions are illustrated in Figure 8.  
Measurements were taken in intervals of 5 m for each scenario until we reached 100% of packet loss. For each location, 100 samples were registered. The SSI measurements were obtained using the _iwlist_ command while the Achievable Throughput was obtained through WBest technology. Besides the two aquatic scenarios, two antenna positions were also evaluated: with the antenna at the drone level (p0) and 15 cm above the drone level (p15); the drone level is 2 cm above water. For the SSI samples obtained, 5% were filtered out to remove outliers. For both metrics, the shaded area represents the 95% confidence interval. Figure 9 illustrates the impact of the distance in the SSI values. As expected, this metric is inversely proportional to the distance, i.e., the SSI decreases with the increase of the distance. In addition, for higher distances, the variation of SSI decreases. Figure 7: USVs software architecture. The antenna position also affects the signal. When the antenna is at the drone level, the aquatic scenario alters the values of SSI for the same distances. The type of curve is maintained but the values are in different ranges. When the antenna is higher, 15 cm above the drone level, the aquatic parameters no longer influence the SSI values, making it a more preferable location to position the antenna in this type of moving elements. For the Network Module in the simulator, we modeled the experienced SSI using the results obtained when the antenna is in the p15 position, resulting in a 4 th degree equation with a Mean Absolute Error (_MAE_) of 0.217, represented in Equation (6), and valid for distances between 5 and 40 m (expressed by \(x\)). With this function, we can accurately simulate the SSI value in simulated scenarios. Figure 8: Two aquatic scenarios: (**top**) AlgaPlus scenario; and (**bottom**) the Water Biological Treatment Plant (WBTP) of the University of Aveiro scenario. Figure 9: Signal Strength Indicator versus distance. Other fits were tried, such as cubic fit with a _MAE_ of 0.269, a quadratic with 1.258, a linear with 2.422, and a logarithmic with 1.179, all of them with higher error than the quartic fit. \[SSI\_est(x)=-0.00002\ x^{4}-0.00051\ x^{3}+0.05896\ x^{2}-2.72277\ x-57.5612, \quad x\in[5,40]. \tag{6}\]  
Figure 10 represents how the Achievable Throughput is influenced by the distance between the two USVs. As expected, the Achievable Throughput is highly affected by the position of the antennas, especially when compared to the impact of the different aquatic scenarios.