## 5 Obtained Results and Evaluation
### Experiment-Based Handover Performance  
In this experiment, we considered a user-centric handover procedure; hence, the serving entities (mmWave and cmWave APs) are used only to provide the necessary data for the robot to make a handover decision. While on a network-scale, the experiment may be envisioned as simply providing WiFi accessibility, handover targeting the preservation of appropriate data session continuity is carried out on the user side. The connection-related performance is displayed in Figure 8, where the horizontal axis represents the timeline of the handover experiment starting from 0 s. With the black, yellow and red vertical lines, the time of the RSSI-based (1), location-aware (2) and preferred (3) handover schemes are indicated, respectively. It is noteworthy that the handover (3) does not correspond to any practical handover schemes, it indicates the preferred handover location that maximizes the throughput while maintaining the link robustness throughout the whole considered robot trajectory in the experiment. Specifically, the RSSI measurements are shown in Figure 8a. It can be observed that the RSSI-based handover scheme switches to mmWave too early, while the location-based scheme is triggered just before the signal strength from the mmWave AP drops. Here, it should be mentioned that the RSSI-based handover performance is displayed for a particular measurement set and is limited by high variations of the WiFi RSSI in the NLoS environment. While adjustment of the hysteresis and time margins might improve the efficiency of the scheme in question, it is more complicated to achieve optimized performance due to the multi-RAT nature of the considered scenario. Similarly, in Figure 8b it is visible that the location-based scheme makes a switch just before the latency issues begin on the mmWave link; hence, it offers better performance than with the RSSI-based handover, which provides higher average throughput. Figure 8: Measurements collected by the robot at the test scenario, (**a**) RSSI measurements; (**b**) WiGig latency measurements; (**c**) physical layer (PHY) rate. Figure 7: Positioning performance via GBP along the robot trajectory in Figure 3b over 2000 trials in the simulation campaign. It is noteworthy that the timeline of Figure 6a is slightly different than that of Figures 8 and 9, which are obtained from the experiment. The reason lies in the fact that the ground truth of the robot trajectory is unknown in the experiment but is defined in the simulation campaign. (**a**) 2D RMSE as a function of time via simulation. (**b**) CDF of positioning error via simulation. For a clear demonstration of the performance difference, we summarize the achieved physical layer (PHY) rate of the robot by both of the considered handover schemes in Figure 8c, in which, we refer to handover (1) as the RSSI-based scheme and handover (2) as the LHO scheme, respectively. It is evident that the maximum rate is achieved when the robot is connected to the mmWave AP, whereas the minimum case is acquired by the WiFi connection. More importantly, our experimental results indicate that over the considered time duration, the handover (2), i.e., the LHO, achieves nearly twice as high average rate (1.523 Gbits/s against 0.806 Gbits/s) than the handover (1) owing to location awareness that maximizes the connected time to the mmWave AP that provides a higher bandwidth, hence a higher throughput. Meanwhile, the link robustness is satisfactory as well since the vertical handover to WiFi was performed before the robot entered the NLoS region w.r.t. the mmWave AP. Ideally, the robot should keep using the mmWave technology as long as possible, due to its higher throughput and lower latency. An early switch to WiFi affects not only the achieved throughput but also delay and jitter, which may become unsatisfactory for delay-sensitive applications, such as telemetry or high-resolution video streaming.