Abstract
Positioning method based on Receive Signal Strength (RSS) is one of the outdoor positioning methods that have a wide range of applications in wireless communication networks. Thus, the main purpose of this paper is to investigate RSS fingerprint-based positioning in cellular wireless networks. In this work, we propose a hybrid algorithm that integrates KNearest Neighbor (KNN) location-based fingerprint approach with fingerprint location estimation based on segmentation approach to improve the positioning accuracy. The performance of the proposed method was evaluated by data that are collected in a dense urban environment. The experimental tests discussed in this paper show that the proposed segmentation-based fingerprinting method provides satisfactory results of localization in an urban environment.
Published Version
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