Indoor Fingerprint Positioning Based on Wi-Fi: An Overview <s> (4) Effects of Mobile Devices <s> Indoor positioning systems that make use of received signal strength based location fingerprints and existing wireless local area network infrastructure have recently been the focus for supporting location-based services in indoor and campus areas. A knowledge and understanding of the properties of the location fingerprint can assist in improving design of algorithms and deployment of position location systems. However, most existing research work ignores the radio signal properties. This paper investigates the properties of the received signal strength reported by IEEE 802.11b wireless network interface cards. Analyses of the data are performed to understand the underlying features of location fingerprints. The performance of an indoor positioning system in terms of its precision is compared using measured data and a Gaussian model to see how closely a Gaussian model may fit the measured data. <s> BIB001 </s> Indoor Fingerprint Positioning Based on Wi-Fi: An Overview <s> (4) Effects of Mobile Devices <s> Considering that indoor positioning applications based on wireless local area network location fingerprinting would be mainly used on the mobile devices. This paper investigates the differences of received signal strength indication (RSSI) between different smart phones and the distributions of RSSI are also analyzed. The statistical analysis of experimental results shows the differences of RSSI between different smart phones are not trivial. Nearly 65% of the RSSI histograms are significantly peaked relative to Gaussian distribution and 65% of them are left-skewed distribution. Therefore, taking skewness and kurtosis coefficients into account, Gaussian distribution is not sufficient to ensure an accurate modeling of the RSSI. The impacts of human behavior on RSSI distribution are explored and two types of human behavior are revealed to be the cause of bi-modal distribution. The statistical data analysis could enable smart phone indoor positioning systems designers to improve positioning performance and to model location fingerprinting based indoor positioning systems. <s> BIB002
Walters BIB002 suggested that the RSS (Received Signal Strength) measured at the same location by dissimilar devices could be different. The real received signal energy is measured in dBm or decibel milliwatt, but researchers generally use RSS measured in dBm as an integer number BIB002 . Different device manufacturers have different standards to convert the real signal energy strength to an RSSI value, which causes differences in RSS measurement that can be large in some cases. In addition to the type of mobile devices, their orientation also has a large impact on the RSS value. Kaemarungsi and Krishnamurthy BIB001 discussed the orientation of mobile devices in their work and found that the RSS values measured by devices oriented in various directions at the same location could be different. They further found that if the device was set behind the APs, the RSS value was the lowest, which decreased by 10 dBm when compared with the highest which was measured when the device was set facing the APs. This indicated that device orientation is crucial and should be considered during RSS measurement.