Evaluation and Comparison of 5G, WiFi, and Fusion With Incomplete Maps for Indoor Localization
Carlos Simón Álvarez-Merino,
Emil J. Khatib,
Hao Qiang Luo-Chen
et al.
Abstract:Precise positioning will play a key role in future 5G/6G services. The upcoming locationbased services drive the necessity of high-precision positioning to indoors. In fingerprinting, which is the most commonly used location algorithm indoors, comprehensive radio maps are essential for a precise localization service and highly influence on the result of the final position of the user. A Machine Learning (ML) algorithm that supports missing reference points information when maps are incomplete that are used dur… Show more
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