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Full-Duplex Cooperative NOMA Short-Packet Communications with K-Means Clustering
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0002-1730-9026
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0003-3604-2766
Queen's University Belfast, United Kingdom.
2023 (English)In: IEEE Workshop on Statistical Signal Processing Proceedings, IEEE Computer Society, 2023, p. 576-580Conference paper, Published paper (Refereed)
Abstract [en]

Fifth-generation (5G) and future sixth-generation (6G) mobile networks aim at offering ultra-reliable, low-latency, and massive machine-type communications. In this context, this paper studies full-duplex (FD) cooperative non-orthogonal multiple access (C-NOMA) short-packet communications (SPC) with K-means clustering of user equipment regarding block error rate (BLER) and sum rate. Analytical expressions are derived for the BLER and sum rate allowing to assess the performance of the considered system. The numerical results reveal the benefits of the FD C-NOMA SPC system, illustrate trade-offs between BLER and sum rate, and show the impact of the transmit signal-to-noise ratio and number of channel uses on the performance. © 2023 IEEE.

Place, publisher, year, edition, pages
IEEE Computer Society, 2023. p. 576-580
Series
IEEE Statistical Signal Processing Workshop (SSP), ISSN 2373-0803, E-ISSN 2693-3551
Keywords [en]
cooperative NOMA, Full-duplex relaying, K-means clustering, short-packet communications, 5G mobile communication systems, Cooperative communication, Economic and social effects, Finite difference method, Signal to noise ratio, Block error rates, Full-duplex, K-means++ clustering, Multiple access, Non-orthogonal, Performance, Short packet communication, Sum-rate
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:bth-25406DOI: 10.1109/SSP53291.2023.10208051ISI: 001051091700117Scopus ID: 2-s2.0-85168910823ISBN: 9781665452458 (print)OAI: oai:DiVA.org:bth-25406DiVA, id: diva2:1798990
Conference
22nd IEEE Statistical Signal Processing Workshop, SSP 2023, Hanoi,July 2-5, 2023.
Available from: 2023-09-20 Created: 2023-09-20 Last updated: 2023-10-26Bibliographically approved

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Chu, Thi My ChinhZepernick, Hans-Juergen

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