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

被引：0

作者：

Al-Habashna, Ala'a ^{[1
]}

Wainer, Gabriel ^{[1
]}

机构：

[1] Carleton Univ, Syst & Comp Engn, Ottawa, ON, Canada

来源：

2020 INTERNATIONAL SYMPOSIUM ON PERFORMANCE EVALUATION OF COMPUTER AND TELECOMMUNICATION SYSTEMS (SPECTS) | 2020年

关键词：

LTE-A; UDNs; RSSI; Fingerprinting;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页数：7

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