# Improving RF Fingerprinting Methods by Means of D2D Communication Protocol
## 1 Introduction and Motivation
The white noise present in the fingerprints in a given location has been usually modeled by a Gaussian distribution centered in the averaged RSS value with a standard deviation around 2-4 dBm depending on the scenario and environment. Although the best distribution tends to be slightly skewed [15], the Gaussian distribution has been well established and widely used in fingerprinting methods. There have been many attempts to minimize this noise, including a more detailed characterization of the RSS values (e.g., by using the Logarithmic Gaussian distance for fingerprint comparison [16]), averaging consecutive fingerprints [17], employing multiple Wi-Fi interfaces to obtain robust averaged fingerprints from independent readings [18], using ensembles as positioning system [19], or applying Gaussian Process Regression Modeling [20], among others. Most of them, requires to increase the computational complexity of the positioning algorithms and, therefore, the energy consumption at the device and/or the remote server side. In this paper, we propose a collaborative method based on device-to-device (D2D) communication to improve the positioning accuracy. The proposed collaborative method is based on the core idea behind the ensemble, and multiple interfaces approach. The probability of having a large, or very large, positioning errors is generally lower when the prediction is based on multiple devices and/or multiple independent predictions. In a place with multiple mobile units nearby (e.g., smartphones), they can be considered independent interconnected sensors for positioning purposes. Each mobile unit could use fingerprinting to roughly estimate its position and D2D communications with other devices to refine the final position estimation by sharing the roughly estimated positions and calculating the estimated distances between the mobile units. Green communication, as energy-efficient communication, is of paramount importance nowadays since the environment protection and energy-saving are inevitable trends [21]. A comprehensive study of energy-efficient tradeoffs involving green communication and wireless was introduced in [22]. Our paper explores the usage of D2D communication to enhance the performance of the indoor positioning systems based on fingerprinting. This approach can be considered simpler and more efficient than those based on multiple-sensor fusion and advanced filtering (Kalman filters and/or Particle filter). Moreover, the positioning accuracy is improved without adding additional infrastructure (namely new Wi-Fi APs or Bluetooth low energy beacons) and, therefore, without increasing the energy consumption of the infrastructure needed for positioning. The remaining of this paper is organized as follows. Section 2 introduces a review of the works related to fingerprinting, collaborative/cooperative positioning and D2D communications. Section 3 describes the basics of the RF fingerprinting technique, D2D communication aspects, Time of Arrival (TOA) of RF signal and the proposed D2D communication assisted RF fingerprint positioning method. Section 4 is devoted to the experimental setup, performance analysis of the proposed method under different conditions and discussion. Section 5 presents the conclusions and draws the research lines for further work.