FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3212618958> ?p ?o ?g. }

• W3212618958 endingPage "1724" @default.
• W3212618958 startingPage "1710" @default.
• W3212618958 abstract "Radio maps provide metrics such as power spectral density for every location in a geographic area and find numerous applications such as UAV communications, interference control, spectrum management, resource allocation, and network planning to name a few. Radio maps are constructed from measurements collected by spectrum sensors distributed across space. Since radio maps are complicated functions of the spatial coordinates due to the nature of electromagnetic wave propagation, model-free approaches are strongly motivated. Nevertheless, all existing schemes for radio occupancy map estimation rely on interpolation algorithms unable to learn from experience. In contrast, this paper proposes a novel approach in which the spatial structure of propagation phenomena such as shadowing is learned beforehand from a data set with measurements in other environments. Relative to existing schemes, a significantly smaller number of measurements is therefore required to estimate a map with a prescribed accuracy. As an additional novelty, this is also the first work to estimate radio occupancy maps using deep neural networks. Specifically, a fully convolutional deep completion autoencoder architecture is developed to effectively exploit the manifold structure of this class of maps." @default.
• W3212618958 created "2021-11-22" @default.
• W3212618958 creator A5048387728 @default.
• W3212618958 creator A5078157470 @default.
• W3212618958 date "2022-03-01" @default.
• W3212618958 modified "2023-10-15" @default.
• W3212618958 title "Deep Completion Autoencoders for Radio Map Estimation" @default.
• W3212618958 cites W1596176149 @default.
• W3212618958 cites W1677182931 @default.
• W3212618958 cites W1973344211 @default.
• W3212618958 cites W1983559465 @default.
• W3212618958 cites W1988642011 @default.
• W3212618958 cites W1994416893 @default.
• W3212618958 cites W2029751976 @default.
• W3212618958 cites W2069041187 @default.
• W3212618958 cites W2089593262 @default.
• W3212618958 cites W2091484400 @default.
• W3212618958 cites W2106703342 @default.
• W3212618958 cites W2108924122 @default.
• W3212618958 cites W2115877982 @default.
• W3212618958 cites W2140452629 @default.
• W3212618958 cites W2144010578 @default.
• W3212618958 cites W2157879939 @default.
• W3212618958 cites W2161280016 @default.
• W3212618958 cites W2164028232 @default.
• W3212618958 cites W2172139273 @default.
• W3212618958 cites W2414995726 @default.
• W3212618958 cites W2543393765 @default.
• W3212618958 cites W2552259797 @default.
• W3212618958 cites W2608018571 @default.
• W3212618958 cites W2620814161 @default.
• W3212618958 cites W2640564155 @default.
• W3212618958 cites W2684068138 @default.
• W3212618958 cites W2712405193 @default.
• W3212618958 cites W2738588019 @default.
• W3212618958 cites W2739846485 @default.
• W3212618958 cites W2792346226 @default.
• W3212618958 cites W2796157935 @default.
• W3212618958 cites W2863849698 @default.
• W3212618958 cites W2889133129 @default.
• W3212618958 cites W2897730733 @default.
• W3212618958 cites W2907414710 @default.
• W3212618958 cites W2964198392 @default.
• W3212618958 cites W2970599193 @default.
• W3212618958 cites W2971736788 @default.
• W3212618958 cites W2998379392 @default.
• W3212618958 cites W2999363952 @default.
• W3212618958 cites W3009073199 @default.
• W3212618958 cites W3013991264 @default.
• W3212618958 cites W3015691456 @default.
• W3212618958 cites W3017212375 @default.
• W3212618958 cites W3040720041 @default.
• W3212618958 cites W3046067353 @default.
• W3212618958 cites W3094539441 @default.
• W3212618958 cites W3133465808 @default.
• W3212618958 cites W4233518571 @default.
• W3212618958 cites W4239343612 @default.
• W3212618958 cites W595252221 @default.
• W3212618958 cites W640676175 @default.
• W3212618958 doi "https://doi.org/10.1109/twc.2021.3106154" @default.
• W3212618958 hasPublicationYear "2022" @default.
• W3212618958 type Work @default.
• W3212618958 sameAs 3212618958 @default.
• W3212618958 citedByCount "15" @default.
• W3212618958 countsByYear W32126189582022 @default.
• W3212618958 countsByYear W32126189582023 @default.
• W3212618958 crossrefType "journal-article" @default.
• W3212618958 hasAuthorship W3212618958A5048387728 @default.
• W3212618958 hasAuthorship W3212618958A5078157470 @default.
• W3212618958 hasBestOaLocation W32126189582 @default.
• W3212618958 hasConcept C101738243 @default.
• W3212618958 hasConcept C108583219 @default.
• W3212618958 hasConcept C115961682 @default.
• W3212618958 hasConcept C137800194 @default.
• W3212618958 hasConcept C154945302 @default.
• W3212618958 hasConcept C202311505 @default.
• W3212618958 hasConcept C31972630 @default.
• W3212618958 hasConcept C41008148 @default.
• W3212618958 hasConcept C76155785 @default.
• W3212618958 hasConceptScore W3212618958C101738243 @default.
• W3212618958 hasConceptScore W3212618958C108583219 @default.
• W3212618958 hasConceptScore W3212618958C115961682 @default.
• W3212618958 hasConceptScore W3212618958C137800194 @default.
• W3212618958 hasConceptScore W3212618958C154945302 @default.
• W3212618958 hasConceptScore W3212618958C202311505 @default.
• W3212618958 hasConceptScore W3212618958C31972630 @default.
• W3212618958 hasConceptScore W3212618958C41008148 @default.
• W3212618958 hasConceptScore W3212618958C76155785 @default.
• W3212618958 hasFunder F4320323299 @default.
• W3212618958 hasIssue "3" @default.
• W3212618958 hasLocation W32126189581 @default.
• W3212618958 hasLocation W32126189582 @default.
• W3212618958 hasOpenAccess W3212618958 @default.
• W3212618958 hasPrimaryLocation W32126189581 @default.
• W3212618958 hasRelatedWork W2159052453 @default.
• W3212618958 hasRelatedWork W2566616303 @default.
• W3212618958 hasRelatedWork W2669956259 @default.
• W3212618958 hasRelatedWork W2734887215 @default.

• next