## 5 Experiments
### Analysis of Results  
After performing the sessions of measures and the post-processing of the RSSI values, we obtain a set of distances between the anchors and the PAN active nodes (blind nodes). These are then used to compute the distances among the PAN nodes and estimate the RSSI values of the network channel links. Table 3 presents the actual values of these distances for each scenario. Since the relative distances are now known, we can compute the link budget for these links using the relative equation with the appropriate propagation model so that we obtain the path loss from Equations (16) and (18). The chip producer provides an absolute non-calibrated accuracy range equal to \(\pm 4\) dB for the hardware CC2530 used in our experiments. On the basis of this accuracy, we can compute the range of RSSI values for each link starting from the actual values. These actual RSSI ranges are shown in Table 4. The key results are also presented through bar graphics in Figures 8 and 9. The first shows the percentage of distance error, before and after the application of proposed method, for all scenarios. The second shows the percentage of RSSI error, again before and after the application of proposed method, for all scenarios. \begin{table}
\begin{tabular}{|c|c|c|c|c|c|c|c|c|c|} \hline \multicolumn{2}{|c|}{**Node**} & \multicolumn{3}{|c|}{**Multilateration—Error**} & \multicolumn{3}{|c|}{**Proposed method—Error**} \\
**TX** & **RX** & **RSSI** & **distance** & **RSSI** & **distance** & **RSSI** \\  & & **[dB]** & **a.v.[m]** & **[\%]** & **a.v.[dB]** & **[\%]** & **a.v.[m]** & **[\%]** & **a.v.[dB]** & **[\%]** \\ \hline \multicolumn{2}{|c|}{**Conference room**} \\ \hline
00-00 & 28-1F & 10 \(\div\) 18 & 0.25 & 7.6\% & 0 & 0\% & 0.33 & 10.3\% & 0 & 0\% \\
00-00 & 95-4C & 18 \(\div\) 26 & 0.96 & 77.4\% & 2 & 7.7\% & 0.73 & 49.6\% & 0 & 0\% \\
00-00 & 1E-57 & 12 \(\div\) 20 & 0.98 & 43.9\% & 0 & 0\% & 0.96 & 42.7\% & 0 & 0\% \\
95-4C & 28-1F & 16 \(\div\) 24 & 0.06 & 0.7\% & 0 & 0\% & 0.62 & 19.7\% & 0 & 0\% \\
28-1F & 1E-57 & 9 \(\div\) 17 & 0.04 & 1.1\% & 0 & 0\% & 0.33 & 10.1\% & 0 & 0\% \\
95-4C & 1E-57 & 6 \(\div\) 14 & 1.33 & 42.5\% & 0 & 0\% & 0.89 & 24.9\% & 0 & 0\% \\ \hline \multicolumn{2}{|c|}{**mean**} & 0.60 & 28.9\% & 0.33 & 1.3\% & 0.64 & 26.2\% & 0 & 0\% \\ \multicolumn{2}{|c|}{**variance**} & 0.55 & 30.9\% & 0.56 & 0.1\% & 0.27 & 16.6\% & 0 & 0\% \\ \hline \end{tabular}
\end{table} 
Table 4: Error on the distance and RSSI estimations obtained using 10 anchors. \begin{table}
\begin{tabular}{l c c c} \hline
**Node tx** & **Node rx** & **Conference room** & **Office** & **Flat** \\ \hline
00-00 & 28-1F & 3.52 m & 3.14 m & 7.11 m \\
00-00 & 95-4C & 2.20 m & 2.08 m & 5.36 m \\
00-00 & 1E-57 & 3.21 m & 2.85 m & 3.87 m \\
95-4C & 28-1F & 2.52 m & 1.78 m & 3.38 m \\
28-1F & 1E-57 & 3.59 m & 1.11 m & 3.36 m \\
95-4C & 1E-57 & 4.46 m & 2.31 m & 3.78 m \\ \hline \end{tabular}
\end{table} 
Table 3: Actual distances among the nodes for the three scenarios. As discussed in Section 3.1, we applied the multilateration algorithm using to ten anchors measurements to achieve the first estimation of blind nodes positions, from which we then computed the relative distance among them. Then we computed the link budget from these relative distances by applying the appropriate propagation models to the path loss. We first analyze the results obtained with the multilateration algorithm using only the OLS, which are shown in the \"multilateration\"columns of