Vision-Aided Dynamic Blockage Prediction for 6G Wireless Communication Networks

Gouranga Charan, Muhammad Alrabeiah, Ahmed Alkhateeb

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

1 Scopus citations

Abstract

Unlocking the full potential of millimeter-wave and sub-terahertz wireless communication networks hinges on realizing unprecedented low-latency and high-reliability requirements. The challenge in meeting those requirements lies partly in the sensitivity of signals in the millimeter-wave, and sub-terahertz frequency ranges to blockages. One promising way to tackle that challenge is to help a wireless network develop a sense of its surrounding using machine learning. This paper attempts to do that by utilizing deep learning and computer vision. It proposes a novel solution that proactively predicts dynamic link blockages. More specifically, it develops a deep neural network architecture that learns from observed sequences of RGB images and beam-forming vectors how to predict possible future link blockages. The proposed architecture is evaluated on a publicly available dataset that represents a synthetic dynamic communication scenario with multiple moving users and blockages. It scores a link-blockage prediction accuracy in the neighborhood of 86%, a performance that is unlikely to be matched without utilizing visual data.

Original languageEnglish (US)
Title of host publication2021 IEEE International Conference on Communications Workshops, ICC Workshops 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728194417
DOIs
StatePublished - Jun 2021
Event2021 IEEE International Conference on Communications Workshops, ICC Workshops 2021 - Virtual, Online
Duration: Jun 14 2021Jun 23 2021

Publication series

Name2021 IEEE International Conference on Communications Workshops, ICC Workshops 2021 - Proceedings

Conference

Conference2021 IEEE International Conference on Communications Workshops, ICC Workshops 2021
CityVirtual, Online
Period6/14/216/23/21

Keywords

  • blockage prediction
  • computer vision
  • Deep learning
  • mmWave
  • terahertz

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management

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