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Performance Comparison of Interpolation Methods for Enriching WiFi Fingerprint Database

Published: 22 January 2025 Publication History

Abstract

Recently, WiFi Fingerprinting-based indoor positioning systems have gained significant attention due to the low cost of infrastructure deployment. In the data collection process, a higher density of reference points may lead to better positioning results. However, it makes this process time-consuming and laborious. To solve this problem, this study applies and compares different interpolation methods to enrich the fingerprint database without increasing the cost of the collection process. To evaluate the performance of the chosen methods, five interpolation methods are implemented in a multi-condition WiFi Fingerprinting dataset. Moreover, to check the robustness of the methods, different numbers of reference points are considered when creating the new interpolated fingerprint databases. According to the results, inverse distance weighting (IDW) is the most suitable interpolation method with low complexity and stable performance. The IDW-based database achieves an average interpolation error of less than 6 dBm compared to the original database. When applying this interpolated database to perform positioning tasks, it helps reduce the collection cost by 30% with slightly lower positioning results compared to the original database. This work demonstrates the feasibility of using interpolation to ease the data collection process of WiFi Fingerprinting, especially in complex and big areas such as airports or hospitals.

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  1. Performance Comparison of Interpolation Methods for Enriching WiFi Fingerprint Database

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    CCIOT '24: Proceedings of the 2024 9th International Conference on Cloud Computing and Internet of Things
    November 2024
    150 pages
    ISBN:9798400717161
    DOI:10.1145/3704304
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 22 January 2025

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    Author Tags

    1. Data Collection
    2. Indoor Positioning System
    3. Interpolation
    4. WiFi Fingerprinting
    5. Wireless Communication

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    • Research-article

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    • National Natural Science Foundation of China
    • National Natural Science Foundation of Hunan Province

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    CCIOT 2024

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