# Improving RF Fingerprinting Methods by Means of D2D Communication Protocol
## 5 Conclusions  
This paper mainly focused on the advantage of using D2D communication features in the RF fingerprint positioning method. Experiments were done on a dedicated RF fingerprint database where the measurement was very accurate and reflected all most all the real world aspects. Since the database does not contain TOA information we had to emulate that by true physical distance, and that has been supported by the proper literature. The main contribution of this paper is to invent a procedure to verify the RF fingerprint positioning information with true value in order to eliminate noisy answer from the system. Through the proposed method about 44% better mean 3D positioning accuracy  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Value of \(\delta\)**} & **Amount of** & **Mean 3D** \\  & **Test Fingerprints** & **Positioning Error** \\ \hline \textless{}0.5 m & 575 & 3.92 m \\ \textless{}0.5 m to \textless{}1 m & 360 & 4.61 m \\ \textless{}2 m & 450 & 4.73 m \\ \textless{}3 m to \textless{}3 m & 197 & 5.29 m \\ \textless{}4 m to \textless{}4 m & 120 & 5.86 m \\ \textless{}5 m & 65 & 6.53 m \\ \textgreater{}5 m & 93 & 8.20 m \\ \hline \hline \end{tabular}
\end{table}
Table 1: Relationship between error indicator and positioning error.  
Figure 14: Floor detection rate (%) of the traditional fingerprinting and D2D-based proposed methods.  
was achieved. Positioning accuracy for the different D2D communication scenario was evaluated. It has been observed that motion and distance among the devices do not hamper the proposed idea. Moreover, according to the presented results, it seems that the motion direction has not a huge impact on the system accuracy. However, by increasing the amount of measurement better accuracy can be achieved, i.e., better results can be obtained by using more measurements between the two devices. Although increasing the number of measurements from three to seven reduces the positioning error in around a 13% (from 5.59 m to 4.83 m), this increase is at the expense of increasing the computational burden around a 40% (from 520 ms to 720 ms). If the accuracy and the computational burden are balanced, the optimal number of measurements is between 3 and 4.  
Apart from TOA, the true physical distance among the devices can be measured by sound, infrared light, camera flash, the signal strength of D2D communication, etc. In the future, we shall try to transfer the calculation burden to the eNB side. Instead of D2D distance, we will explore the UE-eNB true distance, which can also be used to verify the RF fingerprint positioning output. Finally, as further work, we will consider to include power consumption restrictions in the indoor positioning systems due to the rising interest in developing more energy-efficient protocols and algorithms to reduce their economic and environmental impact and promote Green Communications.  
S.K. conceived, designed and performed the experiments; S.K. and [PERSON] wrote the paper. [PERSON] and [PERSON] guided the paper writing and reviewed the paper. All authors read, revised and approved the final manuscript after the peer-reviewing process.  
[PERSON] express his warm thanks to [PERSON] foundation for its financial support. [PERSON] gratefully acknowledges funding from European Union's Horizon 2020 Research and Innovation programme under the [PERSON] grant agreement No. 813278 (A-WEAR: A network for dynamic wearable applications with privacy constraints, [[http://www.a-wear.eu/](http://www.a-wear.eu/)]([http://www.a-wear.eu/](http://www.a-wear.eu/))).  
The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.