RSSI-based Indoor Localization with LTE-A Ultra-Dense Networks

Indoor localization has received attention due to the emergence of location-based mobile applications. In addition to mobile application, indoor localization can be used for other purposes, such as optimization of building operations. We present new models to study the performance of a localization method based on the Received Signal Strength Indicator (RSSI), using Long Term Evaluation-Advanced (LTE-A) Ultra Dense Networks (UDNs). Our approach provides a localization technique with existing infrastructure. Fingerprinting is used to estimate the location of User Equipment (UE) in a building from their RSSI value. The simulation results show that LTE-A UDNs can provide good accuracy for indoor location.