# Communication Interface Manager for Improving Performance of Heterogeneous UAV Networks
## 6 Obtained Results
### MAC and PHY Evaluation
Theoretically, the Rx power would be \(-69\) dBm, resulting in 16.02 dBm (power applied in the 802.11 transceivers used (Table 2)) minus the 85 dB maximum of loss in Figure 12.  
Figure 13 presents the RSSI and noise aggregated samples received by the network during the experiments. Here, the IM presents the lowest variation in RSSI in the three experimental scenarios, which implies more stable connections between the nodes. The RSSI remained in the range of \(-38\) to \(-34\) dBm in the three-node experiment scenario, from \(-34\) to \(-30\) dBm in the the five-node scenario, and from \(-50\) to \(-48\) dBm in the eight-nodes scenario, allowing greater connectivity of the nodes during the flight. The intensity of the received noise showed low variation throughout the experiments, remaining in the range of \(-92\), \(-94\), and \(-96\) dBm considering the background noise and the noise caused by the co-channel interference between the nodes, since they used the same channel for communication for both interfaces in all experiments (homogeneous and heterogeneous). The intensity of the connection in levels can be verified from the result obtained by the RSSI network subtracting its average values of \(-38\) dBm (three nodes), \(-34\) dBm (five nodes), and \(-50\) dBm (eight nodes) by the average noise obtained \(-92\), \(-94\), and \(-96\) dBm, respectively. In this case, we obtained \(-54\), \(-60\), and \(-46\) dBm network RSSIs, respectively. So, on scale of 0 to \(-100\) (with 0 meaning the best signal possible and \(-100\) indicating the worst), the IM presented an RSSI value of around 50, which is generally considered to be good enough for most users and online activities. The SNR was calculated from the average values of the RSSI and noise obtained by the network: 0.41 (three nodes), 0.36 (five nodes), and 0.52 (eight nodes) network average signal gain. Figure 14 shows the message delays considering interval samples of 10 ms. The delay measurements occurred until reaching the maximum distance between nodes. The label containing the IM decisions is shown up to 150,000 samples for the five- and eight-node scenarios. It caused the IM to not change the use of the last chosen interface. Thus, in the three-node scenarios, the IM presented better performance for delay measurements, with an average 10 ms delay up to 200,000 samples (around a 20 m distance between nodes). After 200,000 samples, we observed a peak delay of 220 ms, which decreased soon after. For delay validation, only the trajectory to the UAV reaching its maximum distance in relation to the starting point was considered. For the five-node scenario, we observed an IM performance similar to that of 802.11p, increasing the delay after 60,000 samples at 10 ms (approximately 16 m distance between nodes) and starting an ascendant curve after 100,000 samples (approximately 30 m distance between nodes). The 802.11n interface presented better performance, increasing the delay only after 150,000 samples (approximately 35 m distance between nodes). Notably, this scenario contained a larger area to be covered by the UAVs, which due to the existence of secondary waypoints and to the greater number of nodes, more messages are generated, increasing the aggregated delay. Then, some nodes may have already started returning to the starting point while others were still on the way. For the eight-node scenario, all the experiments presented 12-30 ms delays up to 150,000 samples (approximately 50 m distance between nodes). In this scenario, the UAV trajectories were sparser but in straight lines (only had start and end waypoints) reaching up 100 m distances between nodes. Therefore, after 200,000 samples, an ascendant curve started up to a 80 ms delay, as the nodes reached their maximum distance.