Distribution of WLAN Received Signal Strength Indication for Indoor Location Determination
Kamol Kaemarungsi
Abstract
Kamol Kaemarungsi
Abstract
Indoor positioning systems are platforms required to provide location information for indoor location-aware computing. This study focuses on a type of indoor positioning systems called location fingerprinting technique that utilizes received signal strength indication (RSSI) of wireless local area network (WLAN) interfaces. Thus far, many characteristics of RSSI have not been thoroughly investigated. Many researchers have relied on the RSSI as sensor information to determine objects location while ignoring the characteristic of RSSI. Therefore, this paper looks into underlying mechanism of RSSI from the indoor positioning systems perspective. In particular, the distributions of RSSI from five different IEEE 802.11b/g WLAN interfaces are investigated using extensive measurement experiments. Desired properties of WLAN interfaces for location fingerprinting are also identified based on the measurement results. The ultimate goal is to use additional knowledge gained here to improve positioning performance and to model location fingerprinting based indoor positioning systems.
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Indoor positioning systems are platforms required to provide location information for indoor location-aware computing. This study focuses on a type of indoor positioning systems called location fingerprinting technique that utilizes received signal strength indication (RSSI) of wireless local area network (WLAN) interfaces. Thus far, many characteristics of RSSI have not been thoroughly investigated. Many researchers have relied on the RSSI as sensor information to determine objects location while ignoring the characteristic of RSSI. Therefore, this paper looks into underlying mechanism of RSSI from the indoor positioning systems perspective. In particular, the distributions of RSSI from five different IEEE 802.11b/g WLAN interfaces are investigated using extensive measurement experiments. Desired properties of WLAN interfaces for location fingerprinting are also identified based on the measurement results. The ultimate goal is to use additional knowledge gained here to improve positioning performance and to model location fingerprinting based indoor positioning systems.
Key concepts: Received signal strength indication, Computer science, Hybrid positioning system, Signal strength, Indoor positioning system, Wi-Fi, Real-time computing, Wireless lan