# RSS Indoor Localization Based on a Single Access Point
## 5 Performance Evaluation  
The proposed methodology was implemented for all 11 Scenarios. For testing purposes, the sample size of the test points was determined at 48 for WKNN and 53 for MMSE localization algorithms. The aforementioned samples were selected with a \"Simple Random Sample\" procedure, as presented in [13]. The calculated mean error and Circular Error Probable (CEP) 95% for both WKNN and MMSE localization algorithms are presented in Table 3 and Figures 6 and 7, respectively. The quality correlation score (CS) for each radiomap is illustrated in Figure 8.  
Figure 4: Multipath effect in indoor environment (Rx Cell 198).  
Figure 5: Time delay profile vs. antenna polarization, H090 and H045.  
Figure 3: Radiomap vs. antenna polarization, H090 and H045.  
Based on the aforementioned results, a significant variation of the localization accuracy can be observed, which depends on the transmitter configuration setup. Scenarios of special interest are Numbers 4 and 6 (marked with a circle) and Scenario No. 2, illustrated with a triangular marker. When implementing WKNN (\(k=4\)), the mean error varies from 1.69 m for Scenario No. 6, and 1.91 m for Scenarios 2 and 4, to 3.25 m for Scenario No. 12. Similar behaviour can be noted for the mean error achieved when utilizing the MMSE (\(\sigma=9\)) algorithm. We recorded a minimum mean error of 2.11 m for Scenario No. 4 and 2.29 m for Scenario No. 6, to a maximum of 3.09 m for Scenario No. 11. The quality evaluation of the candidate radiomaps supports the above findings, indicating that the most appropriate radiomaps in this setup are No. 6 (\(CS=0.314\)) and No. 4 (\(CS=0.355\)). The localization accuracy that can be achieved with the proposed methodology is comparable with the benchmark Scenario No. 1, where five APs were used. More specifically, although utilizing the information from five different APs leads to a minimum of 1.04 m mean error, the 1.69 m error still able to be accomplished by a single, two-antenna AP appears to be satisfactory for performing RSS fingerprint localization in small areas, like residential environments. Typical residential applications may include remote monitoring of patients, elderly people, children, and animals. Such localization solutions could be also integrated in smart homes, where different sensors can be activated depending on the proximity of the user. Another observation that is worth mentioning is related to Scenario 2, where the configuration of both antennas was set to Vertical Polarization. The RSS differences occurred only due to the spacial separation of the antennas. On the other hand, it is noted that Scenario numbers 4 and 6, which performed best, were configured with antennas at 45 degrees. Finally, it can be safely assumed that by utilizing various MIMO configurations and a proper antenna polarization configuration, localization accuracy will be improved.  
\begin{table}
\begin{tabular}{l c c c c c c c c c c c} \hline \hline
**Decision Factor** & **2** & **3** & **4** & **5** & **6** & **7** & **8** & **9** & **10** & **11** & **12** \\ \hline WKNN Mean Error (m) & 1.91 & 2.21 & 1.91 & 1.98 & 1.69 & 2.09 & 2.27 & 2.72 & 3.01 & 2.67 & 3.25 \\ WKNN CEP 95\% (m) & 3.41 & 4.27 & 3.69 & 3.36 & 3.45 & 3.48 & 6.22 & 4.45 & 2.99 & 9.00 & 9.85 \\ MMSE Mean Error (m) & 2.17 & 2.48 & 2.11 & 2.49 & 2.29 & 2.55 & 2.82 & 2.71 & 3.08 & 3.09 & 2.52 \\ MMSE CEP 95\% (m) & 3.78 & 4.14 & 4.19 & 5.60 & 4.27 & 4.37 & 4.97 & 4.54 & 6.07 & 5.86 & 5.01 \\ Correlation Score & 0.371 & 0.440 & 0.355 & 0.363 & 0.314 & 0.398 & 0.442 & 0.525 & 0.591 & 0.488 & 0.657 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Localization algorithm performance and correlation score per candidate radiomap.  
Figure 6: WKNN Algorithm performance. (a) Mean error per polarization Scenario; (b) CEP95 per polarization Scenario.