A simple ANN-MLP model for estimating 60-GHz PDP inside public and private vehicles
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU148534" target="_blank" >RIV/00216305:26220/23:PU148534 - isvavai.cz</a>
Result on the web
<a href="https://jwcn-eurasipjournals.springeropen.com/articles/10.1186/s13638-023-02257-0" target="_blank" >https://jwcn-eurasipjournals.springeropen.com/articles/10.1186/s13638-023-02257-0</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1186/s13638-023-02257-0" target="_blank" >10.1186/s13638-023-02257-0</a>
Alternative languages
Result language
angličtina
Original language name
A simple ANN-MLP model for estimating 60-GHz PDP inside public and private vehicles
Original language description
Radio wave propagation in an intra-vehicular (IV) environment is markedly different from other well-studied indoor scenarios, such as an office or a factory floor. While millimetre wave (mmWave)-based intra-vehicular communications promise large bandwidth and can achieve ultra-high data rates with lower latency, exploiting the advantages of mmWave communications largely relies on adequately characterising the propagation channel. Channel characterisation is most accurately done through an extensive channel sounding, but due to hardware and environmental constraints, it is impractical to test channel conditions for all possible transmitter and receiver locations. Artificial neural network (ANN)-based channel sounding can overcome this impediment by learning and estimating the channel parameters from the channel environment. We estimate the power delay profile in intra-vehicular public and private vehicle scenarios with a high accuracy using a simple feedforward multi-layer perception-based ANN model. Such artificially generated models can help extrapolate other relevant scenarios for which measurement data are unavailable. The proposed model efficiently matches the taped delay line samples obtained from real-world data, as shown by goodness-of-fit parameters and confusion matrices.
Czech name
—
Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering
Result continuities
Project
<a href="/en/project/GF23-04304L" target="_blank" >GF23-04304L: Multi-band prediction of millimeter-wave propagation effects for dynamic and fixed scenarios in rugged time-varying environments</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
EURASIP Journal on Wireless Communications and Networking
ISSN
1687-1472
e-ISSN
1687-1499
Volume of the periodical
2023
Issue of the periodical within the volume
1
Country of publishing house
CH - SWITZERLAND
Number of pages
16
Pages from-to
1-16
UT code for WoS article
001002976900001
EID of the result in the Scopus database
2-s2.0-85163081070