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Deep Learning Approaches to Radio Map Estimation

Radio map estimation (RME) is the task of predicting radio power at all locations in a two-dimensional area and at all frequencies in a given band. This thesis explores four deep learning approaches to RME: dual path autoencoders, skip connection autoencoders, diffusion, and joint learning with transmitter localization.

Identiferoai:union.ndltd.org:unt.edu/info:ark/67531/metadc2179342
Date07 1900
CreatorsLocke IV, William Alexander
ContributorsHuang, Yan, Li, Xinrong, Fan, Heng
PublisherUniversity of North Texas
Source SetsUniversity of North Texas
LanguageEnglish
Detected LanguageEnglish
TypeThesis or Dissertation
FormatText
RightsPublic, Locke IV, William Alexander, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved.

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