Environment-Aware Location Estimation in Cellular Networks. (15th January 2008)

• Record Type: Journal Article
• Authors: Türkyılmaz Türkyılmaz, Onur Onur; Alagöz Alagöz, Fatih Fatih; Gür Gür, Gürkan Gürkan; Tugcu Tugcu, Tuna Tuna
• Other Names: Zheng Zheng Rong Rong Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2008-01-15
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/276456
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : We propose a novel mobile positioning algorithm for cellular networks based on the estimation of the radio propagation environment. Since radio propagation characteristics vary in different environments, knowing the environment of the mobile user is essential for accurate Received Signal Strength- (RSS-) based location estimation. The key feature of our method is its capability to estimate the environment of the mobile user using machine learning techniques and to utilize this information for enhancing RSS-based distance calculations. The proposed algorithm, namely, EARBALE, has been evaluated using field measurements collected from a GSM network in diverse geographic locations. Our approach turns out to be significantly beneficial, enhancing estimation accuracy, and thereby enabling high-performance mobile positioning in a practical and cost-effective manner. Additionally, it is computationally light-weight and can be integrated onto any RSS-based algorithm as an enhancement add-on.