Matches in SemOpenAlex for { <https://semopenalex.org/work/W2783108254> ?p ?o ?g. }
Showing items 1 to 87 of
87
with 100 items per page.
- W2783108254 abstract "The use of high frequency millimeter wave (mmWave) bands at 28 GHz or higher will be a defining characteristic of next- generation wireless networks, such as 5G and 802.11ad networks. However, communicating over these high frequencies bands often requires directional antennas on base stations to dynamically align their beams with mobile nodes. To quickly align antennas, we propose a data-driven deep neural network (DNN) approach to localize mobile nodes using lower frequency spectrum. Our methods require fewer than 30 real-world sample locations to learn a model that can localize a mobile node to the required 5G indoor sub-meter accuracy. We demonstrate with real-world data in indoor and outdoor experiments that this performance is achievable, even in multipath-rich environments. Further, we show via simulation that the proposed DNN approach is robust to noise and collinearity between antenna arrays. Our primary contributions are: (1) a novel structure for a deep neural network that reflects the impact base station location has on node localization, (2) a quantized loss function for neural network training that improves localization accuracy and reduces the amount of training data needed, and (3) a procedure for using synthetic data to reduce the required number of real-world measurements needed for training the data-driven localization model. Our real-world experiments show that the use of synthetic data can improve localization accuracy by over 3x." @default.
- W2783108254 created "2018-01-26" @default.
- W2783108254 creator A5024976185 @default.
- W2783108254 creator A5051324676 @default.
- W2783108254 creator A5066867900 @default.
- W2783108254 date "2017-12-01" @default.
- W2783108254 modified "2023-09-25" @default.
- W2783108254 title "A Data-Driven Approach to Localization for High Frequency Wireless Mobile Networks" @default.
- W2783108254 cites W1504983838 @default.
- W2783108254 cites W1964624959 @default.
- W2783108254 cites W2063989678 @default.
- W2783108254 cites W2074011868 @default.
- W2783108254 cites W2128131274 @default.
- W2783108254 cites W2296766323 @default.
- W2783108254 cites W2309512289 @default.
- W2783108254 cites W2507151029 @default.
- W2783108254 cites W2786399413 @default.
- W2783108254 doi "https://doi.org/10.1109/glocom.2017.8254732" @default.
- W2783108254 hasPublicationYear "2017" @default.
- W2783108254 type Work @default.
- W2783108254 sameAs 2783108254 @default.
- W2783108254 citedByCount "12" @default.
- W2783108254 countsByYear W27831082542018 @default.
- W2783108254 countsByYear W27831082542019 @default.
- W2783108254 countsByYear W27831082542020 @default.
- W2783108254 countsByYear W27831082542021 @default.
- W2783108254 countsByYear W27831082542022 @default.
- W2783108254 countsByYear W27831082542023 @default.
- W2783108254 crossrefType "proceedings-article" @default.
- W2783108254 hasAuthorship W2783108254A5024976185 @default.
- W2783108254 hasAuthorship W2783108254A5051324676 @default.
- W2783108254 hasAuthorship W2783108254A5066867900 @default.
- W2783108254 hasConcept C108037233 @default.
- W2783108254 hasConcept C127162648 @default.
- W2783108254 hasConcept C127413603 @default.
- W2783108254 hasConcept C154945302 @default.
- W2783108254 hasConcept C161218011 @default.
- W2783108254 hasConcept C31258907 @default.
- W2783108254 hasConcept C41008148 @default.
- W2783108254 hasConcept C50644808 @default.
- W2783108254 hasConcept C555944384 @default.
- W2783108254 hasConcept C62611344 @default.
- W2783108254 hasConcept C66938386 @default.
- W2783108254 hasConcept C68649174 @default.
- W2783108254 hasConcept C76155785 @default.
- W2783108254 hasConcept C79403827 @default.
- W2783108254 hasConceptScore W2783108254C108037233 @default.
- W2783108254 hasConceptScore W2783108254C127162648 @default.
- W2783108254 hasConceptScore W2783108254C127413603 @default.
- W2783108254 hasConceptScore W2783108254C154945302 @default.
- W2783108254 hasConceptScore W2783108254C161218011 @default.
- W2783108254 hasConceptScore W2783108254C31258907 @default.
- W2783108254 hasConceptScore W2783108254C41008148 @default.
- W2783108254 hasConceptScore W2783108254C50644808 @default.
- W2783108254 hasConceptScore W2783108254C555944384 @default.
- W2783108254 hasConceptScore W2783108254C62611344 @default.
- W2783108254 hasConceptScore W2783108254C66938386 @default.
- W2783108254 hasConceptScore W2783108254C68649174 @default.
- W2783108254 hasConceptScore W2783108254C76155785 @default.
- W2783108254 hasConceptScore W2783108254C79403827 @default.
- W2783108254 hasLocation W27831082541 @default.
- W2783108254 hasOpenAccess W2783108254 @default.
- W2783108254 hasPrimaryLocation W27831082541 @default.
- W2783108254 hasRelatedWork W1983292184 @default.
- W2783108254 hasRelatedWork W1988874032 @default.
- W2783108254 hasRelatedWork W2004299095 @default.
- W2783108254 hasRelatedWork W2005124319 @default.
- W2783108254 hasRelatedWork W2026436689 @default.
- W2783108254 hasRelatedWork W2026980867 @default.
- W2783108254 hasRelatedWork W2037230040 @default.
- W2783108254 hasRelatedWork W2062327056 @default.
- W2783108254 hasRelatedWork W2125955734 @default.
- W2783108254 hasRelatedWork W2133762042 @default.
- W2783108254 hasRelatedWork W2136721983 @default.
- W2783108254 hasRelatedWork W2167037659 @default.
- W2783108254 hasRelatedWork W2189121979 @default.
- W2783108254 hasRelatedWork W2332599982 @default.
- W2783108254 hasRelatedWork W2774949509 @default.
- W2783108254 hasRelatedWork W2911781873 @default.
- W2783108254 hasRelatedWork W2917771750 @default.
- W2783108254 hasRelatedWork W2958130398 @default.
- W2783108254 hasRelatedWork W3005588269 @default.
- W2783108254 hasRelatedWork W3125304350 @default.
- W2783108254 isParatext "false" @default.
- W2783108254 isRetracted "false" @default.
- W2783108254 magId "2783108254" @default.
- W2783108254 workType "article" @default.