# LoRa Architecture for V2X Communication: An Experimental Evaluation with Vehicles on the Move
## 6 Outdoor Testing and Analysis of the Prototypes
### Statistical Analysis of Proposed System  
The aspect of the number of the data points received RSUs along the road needs to be verified since two manipulating factors--order of the RSU and different speeds of the car--are considered in the performance evaluation. As the groups have different spreads, i.e., number of the data points are  
Figure 14: Data points received by each RSU at different speeds of the car _with_ Kalman filter. different for different RSU and speeds, parametric tests are used for statistical analysis [75]. Therefore, the statistical analysis using analysis of variance (ANOVA) is performed with test data to determine how the order of the RSU and speed of the vehicles affect the total number of data packets received by any RSU. Thus, the following assumptions were made for statistical analysis purposes: First, it is assumed that the variation in RSU order will not produce diverse results with respect to the number of data packets received. Further, the tests were randomized to prevent unspecified disturbances that are associated with location, roadside infrastructures, or direct line of sight from being confounded with effects. This allowed for the assumption that errors are independently distributed random variables. A hypothesis is made to determine the effect of the positioning order of the RSU (P-RSU) on the total number of data packets (ND) received by each of them. The speed of the vehicle (VS) remains constant in any single run for all of the RSUs. It is also assumed that all the RSUs receive the same ND irrespective of the P-RSU. With this assumption, a few hypotheses were formulated, including:  
* Null Hypothesis (H\({}_{0}\)): ND on different P-RSU will not vary. * Alternative Hypothesis (H\({}_{\text{A}}\)): Some RSU will receive higher ND than others. * Speed Effects
* Null Hypothesis (H\({}_{0}\)): The speed of the vehicles do not have any effect on the total number of data packets. All of the treatment effects, in this case, are equal to zero. i.e., \(\tau 1=\tau 2=\tau 3=0\). * Alternative Hypothesis (HA): At least of the speeds has a significant effect on the total number of data packets. i.e., at least one of \(\tau\
eq 0\). * Interaction Effects
* Null Hypothesis (H\({}_{0}\)): None of the interactions have any effect on the flow rate. * Alternative Hypothesis (HA): At least one interaction has a significant effect on the flow rate. The data analysis started with the assumption that the interaction of P-RSU and VS does not have a significant effect on the ND. A study was performed to identify the various methods by which the significance of interactions can be found to find this interaction effect. Two factorial design with replication is determined to be the test method as the data are collected in multiple trials and as there were two factors in the test- P-RSU and VS. The data used to perform these two factorial tests is shown in Table 4 for three different P-RSU (RSU1, RSU 2, RSU 3) and five different VS (15 kmph, 25 kmph, 30 kmph, 40 kmph, 50 kmph). A general factorial design test is performed on the above data and Table 5 depicts the ANOVA results. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & & **VS** & & \\ \cline{2-5}
**P-RSU** & **15 kmph** & **25 kmph** & **30 kmph** & **40 kmph** & **50 kmph** \\ \cline{2-5}  & & & ND & & \\ \hline  & 12 & 10 & 8 & 8 & 6 \\ RSU 1 & 13 & 10 & 9 & 8 & 6 \\  & 12 & 10 & 8 & 8 & 6 \\ \hline  & 13 & 11 & 8 & 8 & 6 \\ RSU 2 & 13 & 10 & 9 & 8 & 5 \\  & 12 & 10 & 9 & 8 & 6 \\ \hline  & 12 & 10 & 8 & 8 & 6 \\ RSU 3 & 12 & 10 & 9 & 8 & 6 \\  & 12 & 10 & 8 & 8 & 6 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Data used in two factorial design tests. The results show that \(p\)-values for P-RSU and interaction are 0.611496 and 0.59726 which are greater than the assumed \(\alpha\) = 0.05. These results suggest accepting the null hypothesis for both P-RSU and interaction effects.