Deep Learning based Power Delay Profile Trend Generation: A 60 GHz Intra-Vehicle Case Study
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU146130" target="_blank" >RIV/00216305:26220/22:PU146130 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9887316" target="_blank" >https://ieeexplore.ieee.org/document/9887316</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/AP-S/USNC-URSI47032.2022.9887316" target="_blank" >10.1109/AP-S/USNC-URSI47032.2022.9887316</a>
Alternative languages
Result language
angličtina
Original language name
Deep Learning based Power Delay Profile Trend Generation: A 60 GHz Intra-Vehicle Case Study
Original language description
In this article we have utilized deep learning (DL) for channel sounding application in the millimeter wave (mmWave) band. Using data from a channel sounding campaign for studying intra-vehicle wireless channels operating over the 55-65 GHz mmWave band, we have trained an artificial neural network (ANN) model, which is used to simulate power-delay-profile (PDP) trends. The required simulation inputs form a minimal set, only comprising the frequency points, the transmitter-receiver distance and the presence of passengers inside car. The simulated PDP trend shows good match with the measured PDP and can be used for constructing tapped-delay-line (TDL) based channel models.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20202 - Communication engineering and systems
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings
ISBN
9781665496582
ISSN
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e-ISSN
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Number of pages
2
Pages from-to
209-210
Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
Colorado State University
Event location
Denver, Colorado
Event date
Jul 10, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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