Publication detail

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.

Original Title

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

Type

conference paper

Language

English

Original Abstract

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.

Keywords

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

Authors

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

Released

15. 7. 2022

Publisher

Institute of Electrical and Electronics Engineers Inc.

Location

Colorado State University

ISBN

9781665496582

Book

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

Pages from

209

Pages to

210

Pages count

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"
}