Deep learning based preamble detection and TOA estimation

Haoran Sun, Aliye Ozge Kaya, Mike MacDonald, Harish Viswanathan, Mingyi Hong

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

Abstract

Accurate Time of Arrival (TOA) estimation has many use cases, including 5G initial access and localization. However, due to multipath propagation and noise, the correlation-based TOA estimation may not be accurate. In this paper, a deep learning based framework is proposed for preamble detection and TOA estimation without the need of knowing the transmit waveform. Extensive simulations on both synthetic data and real measured data show that the proposed method improves prediction accuracy by about three times while keeping the same computational complexity in comparison to the correlation method. It also provides 1000x computational reduction compared to the template matching method without loss of accuracy.

Original languageEnglish (US)
Title of host publication2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728109626
DOIs
StatePublished - Dec 2019
Event2019 IEEE Global Communications Conference, GLOBECOM 2019 - Waikoloa, United States
Duration: Dec 9 2019Dec 13 2019

Publication series

Name2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings

Conference

Conference2019 IEEE Global Communications Conference, GLOBECOM 2019
CountryUnited States
CityWaikoloa
Period12/9/1912/13/19

Keywords

  • Convolutional neural networks
  • Deep learning
  • Preamble detection
  • TOA estimation

Fingerprint Dive into the research topics of 'Deep learning based preamble detection and TOA estimation'. Together they form a unique fingerprint.

  • Cite this

    Sun, H., Kaya, A. O., MacDonald, M., Viswanathan, H., & Hong, M. (2019). Deep learning based preamble detection and TOA estimation. In 2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings [9013265] (2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLOBECOM38437.2019.9013265