Mid Sweden University

miun.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Design and Resource Allocation of NOMA-based Transmission Scheme for Industrial Collaborative AR
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.ORCID iD: 0000-0003-3717-7793
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
Show others and affiliations
2022 (English)In: 2022 IEEE GLOBECOM Workshops, GC Wkshps 2022 - Proceedings, IEEE conference proceedings, 2022, p. 1604-1609Conference paper, Published paper (Refereed)
Abstract [en]

Collaborative augmented reality (AR), which enables interaction and consistency in multi-user AR scenarios, is a promising technology for AR-guided remote monitoring, optimization, and troubleshooting of complex manufacturing processes. However, for uplink high data rate demands in collaborative-AR, the design of an efficient transmission and resource allocation scheme is demanding in resource-constrained wireless systems. To address this challenge, we propose a collaborative non-orthogonal multiple access (C-NOMA)-enabled transmission scheme by exploiting the fact that multi-user interaction often leads to common and individual views of the scenario (e.g., the region of interest). C-NOMA is designed as a two-step transmission scheme by treating these views separately and allowing users to offload the common views partially. Further, we define an optimization problem to jointly optimize the time and power allocation for AR users, with an objective of minimizing the maximum rate-distortion of the individual views for all users while guaranteeing a target distortion of their common view for its mutual significance. For its inherent non-linearity and non-convexity, we solve the defined problem using a primal-dual interior-point algorithm with a filter line search as well as by developing a successive convex approximation (SCA) method. The simulation results demonstrate that the optimized C-NOMA outperforms the non-collaborative baseline scheme by 23.94% and 77.28% in terms of energy consumption and achievable distortion on the common information, respectively. 

Place, publisher, year, edition, pages
IEEE conference proceedings, 2022. p. 1604-1609
Keywords [en]
AR, interior-point filter line search, NOMA, rate-distortion, successive convex approximation (SCA)
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:miun:diva-47508DOI: 10.1109/GCWkshps56602.2022.10008766Scopus ID: 2-s2.0-85146910037ISBN: 9781665459754 (print)OAI: oai:DiVA.org:miun-47508DiVA, id: diva2:1734974
Conference
2022 IEEE GLOBECOM Workshops, GC Wkshps 2022, 4 December 2022 through 8 December 2022
Available from: 2023-02-07 Created: 2023-02-07 Last updated: 2023-02-07Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Khodakhah, FarnazMahmood, AamirAbedin, Sarder FakhrulThar, KyiÖsterberg, PatrikGidlund, Mikael

Search in DiVA

By author/editor
Khodakhah, FarnazMahmood, AamirAbedin, Sarder FakhrulThar, KyiÖsterberg, PatrikGidlund, Mikael
By organisation
Department of Information Systems and Technology
Telecommunications

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 173 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf