Detail publikace

Deep Learning based Power Delay Profile Trend Generation: A 60 GHz Intra-Vehicle Case Study

SHUKLA, R. SARKAR, A. CHANDRA, A. MIKULÁŠEK, T. PROKEŠ, A. JAN M., K. ZIÓŁKOWSKI, C.

Originální název

Deep Learning based Power Delay Profile Trend Generation: A 60 GHz Intra-Vehicle Case Study

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

mmWave channel sounding; intra-vehicle communication; deep learning; power-delay-profile

Autoři

SHUKLA, R.; SARKAR, A.; CHANDRA, A.; MIKULÁŠEK, T.; PROKEŠ, A.; JAN M., K.; ZIÓŁKOWSKI, C.

Vydáno

15. 7. 2022

Nakladatel

Institute of Electrical and Electronics Engineers Inc.

Místo

Colorado State University

ISBN

9781665496582

Kniha

2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings

Strany od

209

Strany do

210

Strany počet

2

URL

https://ieeexplore.ieee.org/document/9887316

BibTex

@inproceedings{BUT179856,
  author="Rajeev {Shukla} and Abhishek Narayan {Sarkar} and Aniruddha {Chandra} and Tomáš {Mikulášek} and Aleš {Prokeš} and Kelner {Jan M.} and Cezary {Ziółkowski}",
  title="Deep Learning based Power Delay Profile Trend Generation: A 60 GHz Intra-Vehicle Case Study",
  booktitle="2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings",
  year="2022",
  pages="209--210",
  publisher="Institute of Electrical and Electronics Engineers Inc.",
  address="Colorado State University",
  doi="10.1109/AP-S/USNC-URSI47032.2022.9887316",
  isbn="9781665496582",
  url="https://ieeexplore.ieee.org/document/9887316"
}