Transformer-driven multi-agent deep reinforcement learning based point cloud video transmissions

Hai Lin, Xianfu Chen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

The point cloud videos, a medium for representing natural content in AR/VR with point clouds, have attracted a wide range of attention for its characteristics and have the potential to be the next generation of video technology. Given the high data volume, the point cloud video raises the challenge of intelligent transmission and resource scheduling in multi-user scenarios under time-varying system conditions. In this paper, we propose a multi-agent deep reinforcement learning (DRL) approach to optimize the expected long-term multi-user QoE and adopt a Field of View (FoV) prediction model with Transformer for high-accuracy FoV prediction. Over the time horizon, the proposed approach learns to select the tiles of the corresponding video in accordance with a proposed well-defined QoE model capable of quantifying users' satisfaction for transmissions in an iterative way. Under various settings, extensive numerical experiments based on real throughput data traces and different computation capabilities data demonstrate that the proposed approach is effective for long-term multi-agent point cloud video transmissions.

Original languageEnglish
Title of host publicationAIIOT 2022 - Proceedings of the 2022 1st Workshop on Digital Twin and Edge AI for Industrial IoT, Part of MobiCom 2022
PublisherAssociation for Computing Machinery ACM
Pages25-30
Number of pages6
ISBN (Electronic)978-1-4503-9784-1
DOIs
Publication statusPublished - 17 Oct 2022
MoE publication typeA4 Article in a conference publication
Event2022 1st Workshop on Digital Twin and Edge AI for Industrial IoT, AIIOT 2022 - Part of MobiCom 2022 - Sydney, Australia
Duration: 21 Oct 2022 → …

Conference

Conference2022 1st Workshop on Digital Twin and Edge AI for Industrial IoT, AIIOT 2022 - Part of MobiCom 2022
Country/TerritoryAustralia
CitySydney
Period21/10/22 → …

Keywords

  • deep reinforcement learning
  • point cloud video
  • quality of experience
  • transformer

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