Channel Gain Cartography via Mixture of Experts
- URL: http://arxiv.org/abs/2012.04290v1
- Date: Tue, 8 Dec 2020 09:06:57 GMT
- Title: Channel Gain Cartography via Mixture of Experts
- Authors: Luis M. Lopez-Ramos, Yves Teganya, Baltasar Beferull-Lozano, Seung-Jun
Kim
- Abstract summary: Most approaches to build such spectrum maps are location-based, meaning that the input variable to the estimating function is a pair of spatial locations.
An alternative location-free approach was recently proposed for spectrum power maps, where the input variable to the maps consists of features extracted from the positioning signals, instead of location estimates.
In this work, apart from adapting the location-free features for the CG maps, a method that can combine both approaches is proposed.
- Score: 18.126535422561766
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: In order to estimate the channel gain (CG) between the locations of an
arbitrary transceiver pair across a geographic area of interest, CG maps can be
constructed from spatially distributed sensor measurements. Most approaches to
build such spectrum maps are location-based, meaning that the input variable to
the estimating function is a pair of spatial locations. The performance of such
maps depends critically on the ability of the sensors to determine their
positions, which may be drastically impaired if the positioning pilot signals
are affected by multi-path channels. An alternative location-free approach was
recently proposed for spectrum power maps, where the input variable to the maps
consists of features extracted from the positioning signals, instead of
location estimates. The location-based and the location-free approaches have
complementary merits. In this work, apart from adapting the location-free
features for the CG maps, a method that can combine both approaches is proposed
in a mixture-of-experts framework.
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