Interpolating a radio map is a problem of great relevance in many scenarios such as network planning, network optimization and localization. In this work such a problem is tackled by leveraging recent results from the emerging field of signal processing on graphs. A technique for interpolating graph structured data is adapted to the problem at hand by using different graph creation strategies, including ones that explicitly consider NLOS propagation conditions. Extensive experiments in a realistic large-scale urban scenario demonstrate that the proposed technique outperforms other traditional methods such as IDW, RBF and model-based interpolation.

Radio Map Interpolation using Graph Signal Processing

REDONDI, ALESSANDRO ENRICO CESARE
2018

Abstract

Interpolating a radio map is a problem of great relevance in many scenarios such as network planning, network optimization and localization. In this work such a problem is tackled by leveraging recent results from the emerging field of signal processing on graphs. A technique for interpolating graph structured data is adapted to the problem at hand by using different graph creation strategies, including ones that explicitly consider NLOS propagation conditions. Extensive experiments in a realistic large-scale urban scenario demonstrate that the proposed technique outperforms other traditional methods such as IDW, RBF and model-based interpolation.
Fingerprinting Localization; Graph Signal Processing; Radio Map Interpolation; Modeling and Simulation; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1034999
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