Enhanced in-building fingerprint positioning using femtocell networks

Abstract

The volume of traffic generated in indoor environments is increasing exponentially, and emerging femtocell networks are being deployed to meet associated challenges. These specific in‐building deployments provide an opportunity for improving the performance of indoor positioning systems. Femtocell networks can be used to support accurate and reliable location services based on received‐ power and fingerprint location techniques. In fingerprint positioning methods, calibration and recalibration procedures are extremely time‐consuming tasks. To address this problem, we developed a novel scenario‐dependent procedure that reduced calibration points. We also analyzed several indoor propagation models, evaluating their suitability to reduce the effort required for calibration as well as their applicability for the recalibration procedures necessary to update previously recorded fingerprints. Our procedure includes both a simulation and a measurement phase, and obtains important improvements in accuracy, precision, and reliability while reducing the time and effort associated with both calibration and recalibration procedures. © 2013 Alcatel‐Lucent.

Enhancing RFID indoor localization with cellular technologies

“…Only particular indoor cellular deployments (such as small cells, low powered base station that can be installed indoors) have been analyzed [8]. In this field, the works [9,10] presented a fingerprint technique based in the mapping and use of radio signals from femtocells (a particular type of small cells) for localization of mobile terminals in indoor environments (few meters). However, such indoor cellular deployments are still not widely implemented and costly.…”

Location-based distributed sleeping cell detection and root cause analysis for 5G ultra-dense networks

“…These are often based on the analysis of the received signal characteristics (e.g., time of arrival, received power, etc.) from different systems such as radio-frequency identification (RFID) [13], WiFi [14], cellular [8], and ultra-wideband (UWB) [15]. Although the use of UE localization has already attracted interest in other OAM tasks, e.g., for the presented MDT cases, it has been mainly neglected in previous self-healing works and particularly for indoor scenarios.…”

“…For example, the knowledge on UEs location is becoming growlingly available in both outdoor and indoor scenarios [7]. Localization mechanisms based on the small cell deployments [8] open the door to using location to support the OAM tasks. Even if its use for self-healing in indoor scenarios has been just recently proposed [9], its usefulness has been previously demonstrated for macrocell scenarios and other OAM tasks (e.g., for coverage optimization [10]).…”

RF-Based Location Using Interpolation Functions to Reduce Fingerprint Mapping

“…Euclidean and Manhattan distances have been used in deterministic location methods [ 8 , 9 , 11 ]. The Euclidean metric is the most widely spread, and its results can be improved taking the most accurate information in the training phase [ 14 , 15 , 16 ], selecting the signal strength level [ 13 ], or introducing fuzzy logic [ 17 ]. Other methods of indoor location combine simultaneously RSSI with additional parameters obtained from physical sensors (movement, acceleration, etc .)…”