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PILA: Sub-Meter Localization Using CSI from Commodity Wi-Fi Devices.

Zengshan Tian1, Ze Li2, Mu Zhou3

  • 1Chongqing Key Lab of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China. tianzs@cqupt.edu.cn.

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Summary
This summary is machine-generated.

This study introduces a novel Wi-Fi indoor localization method using Angle-of-Arrival (AOA) and Received Signal Strength (RSS). The approach achieves a median error of 0.7 meters in real-world indoor settings.

Keywords:
Angle-of-ArrivalChannel State InformationReceived Signal StrengthWi-Fiindoor localization

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Area of Science:

  • Wireless Communication
  • Indoor Localization
  • Signal Processing

Background:

  • Accurate indoor localization is crucial for various applications.
  • Existing Wi-Fi localization methods often struggle with multipath effects and accuracy.
  • Utilizing Channel State Information (CSI) offers a promising avenue for enhanced localization.

Purpose of the Study:

  • To develop a new indoor localization system using Wi-Fi networks.
  • To improve the accuracy of Angle-of-Arrival (AOA) estimation by mitigating multipath interference.
  • To integrate AOA and Received Signal Strength (RSS) for a robust localization solution.

Main Methods:

  • Collected Channel State Information (CSI) using commodity Wi-Fi devices with a custom three-antenna setup to estimate AOA.
  • Developed a direct path identification algorithm to minimize multipath effects on AOA.
  • Formulated a new objective function integrating AOA and RSS, solved using Second-order Cone Programming (SOCP) relaxation for convexity.

Main Results:

  • Successfully estimated AOA of Wi-Fi signals using designed hardware and algorithms.
  • Reduced the impact of multipath interference on AOA estimation.
  • Achieved a median localization error of 0.7 meters in practical indoor environments.

Conclusions:

  • The proposed integrated AOA and RSS localization approach is effective for indoor environments.
  • The use of SOCP relaxation successfully transformed the non-convex localization problem into a convex one.
  • Commodity Wi-Fi devices can be utilized for high-accuracy indoor localization with the developed method.