# Surface Correlation-Based Fingerprinting Method Using LTE Signal for Localization in Urban Canyon
## 1 Introduction  
Recently, the rapid development of wireless communication technology has increased the dependency of human life on location-based services. Reliable localization technology is widely applied to various fields such as gaming, social networking service, industrial safety, as well as current vehicle navigation systems. The most commonly used technology for localization is the Global Satellite Navigation System (GNSS). It is obvious that GNSS is the most efficient and accurate in the outdoor environment. However, in complex urban areas or indoor environments, the accuracy of the GNSS is acutely degraded due to signal unavailability and the multipath fading of the satellite signals [1]. In order to mitigate the limitation of GNSS usage in urban areas, several wireless communication technologies for localization have been developed. In recent years, the Long Term Evolution (LTE) that has become widely used in the metropolitan areas is attracting attention as a means of localizing pedestrians or vehicles in these challenging areas [2; 3; 4]. The assisted-GNSS (A-GNSS) scheme uses assistance data provided by LTE to improve the initial operation of Global Positioning System (GPS)-based devices [5; 6]. However, this scheme does not use LTE signals for localization. The enhanced Cell-ID (e-CID) technology was proposed to improve localization accuracy by adding Round Trip Time-based distance information to the existing Cell-ID method. However, its performance is limited depending on the size of the cell [7; 8]. The Observed Time Difference of Arrival (OTDoA) technology defined in the 3 GPP-LTE Release 9 standard is based on the Time Difference of Arrival (TDoA) method using the positioning reference signal of LTE. This technology estimates a location based on the hyperbolic trilateration of the TDoA measurement, Reference Signal Time Difference (RSTD) [9; 10]. Since the OTDoA technology requires at least three Base Stations (BS) for trilateration, its usage is limited in areas with low BS density. Despite the above-mentioned LTE-based attempts to improve performance, such the technologies are still hard-pressed to satisfy the performance standards, such as accuracy, stability, and availability, required by various LBS services. In Non-Line-of-Sight (NLoS) environments, such as urban areas or indoors, a fingerprinting technology can be more effective than timing-based localization technology. The LTE Positioning Protocol requires that Received Signal Strength (RSS) information be provided as well as CID, Timing Advanced (TA), angle of arrival and channel status information [11; 12]. [PERSON] et al. [13] proposed the use of Observed Time Differences (OTD) with RSS to improve the performance of a fingerprinting-based localization technology. [PERSON] et al. [14] developed a maximum likelihood-based fingerprinting method using RSS, RSTD, and TA of LTE system. It demonstrated that the proposed fingerprinting method is generally superior to the e-CID and OTDOA based localization method. [PERSON] et al. [15] developed a grid-based fingerprinting method using the RSS information of LTE and WLAN. The performance of LTE-based fingerprinting method was improved with the RSS information of WLAN. However, it has been reported that the fingerprinting-based localization technologies based on direct comparison of the measured RSS with fingerprinting database suffer from the lack of accuracy, stability, and robustness [16; 17; 18]. Received RF signals experience many distortion phenomena during propagation and vary consistently due to other RF signal' interference, multipath fading, and noise. The RF signal distortion and variation becomes more prominent in the areas where structures that prohibit direct propagation are densely located and diverse wireless applications are actively used. This is typical in the LTE signal generated in urban areas. In conventional fingerprinting technology that utilizes instantaneous RSS data, these distortion phenomena tend to increase ambiguity.