Reducing location update cost in a PCS network
IEEE/ACM Transactions on Networking (TON)
Personal locator services emerge
IEEE Spectrum
Robotics-based location sensing using wireless ethernet
Proceedings of the 8th annual international conference on Mobile computing and networking
A Statistical Modeling Approach to Location Estimation
IEEE Transactions on Mobile Computing
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Mobile Computing
WLAN Location Determination via Clustering and Probability Distributions
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Design and Analysis of Location Management for 3G Cellular Networks
IEEE Transactions on Parallel and Distributed Systems
Locating Mobile Stations with Statistical Directional Propagation Model
AINA '04 Proceedings of the 18th International Conference on Advanced Information Networking and Applications - Volume 2
IEEE Transactions on Mobile Computing
A Scrambling Method for Fingerprint Positioning Based on Temporal Diversity and Spatial Dependency
IEEE Transactions on Knowledge and Data Engineering
Location sensing and privacy in a context-aware computing environment
IEEE Wireless Communications
Mobility modeling, location tracking, and trajectory prediction in wireless ATM networks
IEEE Journal on Selected Areas in Communications
Dynamic hierarchical mobility management strategy for mobile IP networks
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Neural Networks
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The recent decade has witnessed a rapid growth in wireless communications technology. This study presents a location management scheme for integrated wireless networks and a signal-based positioning algorithm for WLAN. The proposed location management scheme provides location information to obtain from a hierarchical location database to mobile users and LBS providers. Additionally, a signal-based positioning algorithm is developed for indoor positioning based on WLAN received signal strength indication (RSSI). Approximated distribution modeling is applied to calculate the probability of users appearing in training points. This mechanism not only locates a mobile client precisely, but also reduces the cost of locating. A performance evaluation is performed to indicate the effectiveness of the proposed location management method, and provide suitable parameter settings.