Convolutional Neural Networks Based Joint AOA/TOF Estimation

Suhwan Jang, Hyunwook Lee, Chungyong Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes one-dimensional convolutional neural networks (1D CNN) based approach for joint angle of arrival (AOA) and time of flight (TOF) estimation. In the network, received signal vectors which contain phase information are organized as an image and output data are scaled for unbiased learning. Simulation results show robustness against insufficient time slots and has low latency once the training is completed.

Original languageEnglish
Title of host publication2021 International Conference on Electronics, Information, and Communication, ICEIC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728191614
DOIs
Publication statusPublished - 2021 Jan 31
Event2021 International Conference on Electronics, Information, and Communication, ICEIC 2021 - Jeju, Korea, Republic of
Duration: 2021 Jan 312021 Feb 3

Publication series

Name2021 International Conference on Electronics, Information, and Communication, ICEIC 2021

Conference

Conference2021 International Conference on Electronics, Information, and Communication, ICEIC 2021
Country/TerritoryKorea, Republic of
CityJeju
Period21/1/3121/2/3

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (NRF-2019R1A2C1010950).

Publisher Copyright:
© 2021 IEEE.

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management
  • Electrical and Electronic Engineering
  • Instrumentation

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