# RSS Indoor Localization Based on a Single Access Point  
[PERSON]  
1 Department of Electrical Engineering, Eindhoven University of Technology, 5600 Eindhoven, The Netherlands 1  
[PERSON]  
1 Department of Electrical Engineering, Eindhoven University of Technology, 5600 Eindhoven, The Netherlands 1  
[PERSON]  
2 School of Computing, Edinburgh Napier University, Edinburgh EH10 5 DT, UK 21 Department of Electrical Engineering, Eindhoven University of Technology, 5600 Eindhoven, The Netherlands 1  
[PERSON]  
3 Faculty of Pure and Applied Sciences, Open University of Cyprus, Nicosia 2220, Cyprus 3  
angles (AOA) with high accuracy. These processes may also require synchronization of transceivers and calibration of antennas [12]. When it comes to RSS localization, the popularity of the method lies on the utilization of existing wireless communication infrastructure, the simplicity of the localization algorithms, and the achieved levels of accuracy. In RSS fingerprint-based localization, the procedure involves an offline and an on-ine phase. During the offline phase, a dataset of RSS fingerprints, named _a radiomap_, is generated by recording the RSS value of each Access Point (AP) at multiple locations in the area of interest. The RSS values are then calibrated in order to improve the quality of the radio-map [13]. It has been shown that such datasets can be generated rapidly and at a relatively low cost, through the use of a deterministic radio propagation simulator [8; 14; 15]. The conventional approach involves performing time-consuming measurement campaigns in the actual environment [14]. The generated radio-map from such a campaign represents a static snapshot of the APs RSS values at each measured location. It has to be noted that every time the environment or the wireless network is modified, one requires a repeat of the measurements. During the online phase, the Mobile Station (MS) performs real-time RSS measurements. Different positioning algorithms are then applied to identify the best match between the observed RSS fingerprint and the respective mean value of the fingerprints recorded in the radiomap during the offline phase. An overview of typical fingerprint-based methods is provided in [16]. A significant drawback of these systems is that they require the deployment of several APs in order to generate unique fingerprints at each location, in order to achieve satisfactory positioning accuracy [15]. Due to this characteristic, RSS fingerprint-based localization systems cannot be easily utilized in small-scale environments, that is, residential places or open plan spaces, where a single AP is deployed. In this paper, we examine the generation of unique fingerprint radiomaps from a single, multi-antenna AP by exploiting antenna polarization effects and combining these radiomaps into a multi-layer radiomap concept. Result analysis indicates that each antenna from the AP device can be considered as an independent transmitting source. Different polarization configurations are then utilized in order to ensure that RSS values from different antennas, at the same location, are not correlated. The proposed method's performance is evaluated in a two-step procedure, initially by implementing and testing the performance of deterministic and probabilistic algorithms (Weighted k-Nearest-Neighbor--WKNN and Minimum Mean Square Error--MMSE) for a set of different antenna orientations, hence different polarization set-ups. Subsequently, the uniqueness of all candidate radiomaps is examined by calculating the correlation level of each fingerprint pair. High correlation scores indicate high probable localization errors, and vice versa. This method requires the implementation of the \"Tolerance-Based Normal Probability Distribution (TBNPD)\" algorithm [15]. The rest of the paper is organized as follows: Section 2 includes related research work on the impact of polarization. In the same section, an overview of RSS fingerprint-based localization methods and general evaluation techniques are included.