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Accurate signal strength prediction based positioning for indoor WLAN systems

Anvar Narzullaev, Yongwan Park, Ho-Youl Jung

Open publisher page 38 citations

Abstract

With development of IEEE802.11 based Wireless Local Area Networks (WLAN) there are several techniques to provide an accurate estimation of the location of mobile devices in indoor environment were presented. As the only available information at receiver side is the received signal strength indication (RSSI) from each WLAN access points (AP), technique called RSSI fingerprinting was proposed [1]. However one of the main drawbacks of RSSI based location is the extensive calibration phase to build a signal fingerprint.

About this research paper

What this paper is about

With development of IEEE802.11 based Wireless Local Area Networks (WLAN) there are several techniques to provide an accurate estimation of the location of mobile devices in indoor environment were presented. As the only available information at receiver side is the received signal strength indication (RSSI) from each WLAN access points (AP), technique called RSSI fingerprinting was proposed [1]. However one of the main drawbacks of RSSI based location is the extensive calibration phase to build a signal fingerprint.

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OpenAlex reports 38 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

With development of IEEE802.11 based Wireless Local Area Networks (WLAN) there are several techniques to provide an accurate estimation of the location of mobile devices in indoor environment were presented. As the only available information at receiver side is the received signal strength indication (RSSI) from each WLAN access points (AP), technique called RSSI fingerprinting was proposed [1]. However one of the main drawbacks of RSSI based location is the extensive calibration phase to build a signal fingerprint.

Key concepts: Signal strength, Computer science, Received signal strength indication, Fingerprint (computing), Wireless lan, Wi-Fi, SIGNAL (programming language), Fingerprint recognition

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