Joint Data and Active User Detection for Grant-free FTN-NOMA in Dynamic Networks

Weijie YUAN, Nan WU, Jinhong YUAN, Derrick Wing Kwan NG, Lajos HANZO

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

2 Citations (Scopus)

Abstract

Both faster than Nyquist (FTN) signaling and non-orthogonal multiple access (NOMA) are promising next generation wireless communications techniques as a benefit of their capability of improving the system's spectral efficiency. This paper considers an uplink system that combines the advantages of FTN and NOMA. Consequently, an improved spectral efficiency is achieved by deliberately introducing both inter-symbol interference (ISI) and inter-user interference (IUI). More specifically, we propose a grant-free transmission scheme to reduce the signaling overhead and transmission latency of the considered NOMA system. To distinguish the active and inactive users, we develop a novel message passing receiver that jointly estimates the channel state, detects the user activity, and performs decoding. We conclude by quantifying the significant spectral efficiency gain achieved by our amalgamated FTN-NOMA scheme compared to the orthogonal transmission system, which is up to 87.5.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Communications, ICC 2020 : Proceedings
PublisherIEEE
ISBN (Electronic)9781728150895
ISBN (Print)9781728150901
DOIs
Publication statusPublished - Jun 2020
Externally publishedYes
Event2020 IEEE International Conference on Communications, ICC 2020 - Dublin, Ireland
Duration: 7 Jun 202011 Jun 2020

Publication series

NameIEEE International Conference on Communications
Volume2020-June
ISSN (Print)1550-3607

Conference

Conference2020 IEEE International Conference on Communications, ICC 2020
Country/TerritoryIreland
CityDublin
Period7/06/2011/06/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Funding

This work is supported the Australia Research Council Discovery Project (DP190101363) and Linkage Projects (LP 160100708 and LP170101196). D. W. K. Ng is supported by funding from the UNSW Digital Grid Futures Institute, UNSW, Sydney, under a cross-disciplinary fund scheme and by the Australian Research Council’s Discovery Project (DP190101363). L. Hanzo would like to acknowledge the financial support of the Engineering and Physical Sciences Research Council projects EP/Noo4558/1, EP/PO34284/1, COALESCE, of the Royal Society’s Global Challenges Research Fund Grant as well as of the European Research Council’s Advanced Fellow Grant QuantCom.

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