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Error Performance of Sparse Code Multiple Access Networks with Joint ML Detection
KTH, School of Electrical Engineering (EES), Communication Theory.ORCID iD: 0000-0002-5407-0835
2016 (English)In: 2016 IEEE 83RD VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING), IEEE, 2016Conference paper, Published paper (Refereed)
Abstract [en]

This paper investigates error performance of sparse code multiple access (SCMA) networks with multiple access channels (MAC) and broadcast channels (BC). We give the closedform expression for the pairwise error probability (PEP) of joint maximum likelihood (ML) detection for multiuser signals over additive white Gaussian noise (AWGN) and Rayleigh fading channels with an arbitrary number of users and multidimensional codebooks. An upper bound for the average symbol error rate (SER) is calculated. The bound is tight in both AWGN channel and Rayleigh fading channels for high SNR regions. The analytical bounds are compared with simulations, and the results confirm the effectiveness of the analysis for both AWGN and Rayleigh fading channels.

Place, publisher, year, edition, pages
IEEE, 2016.
Series
IEEE Vehicular Technology Conference Proceedings, ISSN 1550-2252
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-197029DOI: 10.1109/VTCSpring.2016.7504241ISI: 000386528400193Scopus ID: 2-s2.0-84979762828ISBN: 978-1-5090-1698-3 (print)OAI: oai:DiVA.org:kth-197029DiVA: diva2:1053112
Conference
IEEE 83rd Vehicular Technology Conference (VTC Spring), MAY 15-18, 2016, Nanjing, PEOPLES R CHINA
Note

QC 20161208

Available from: 2016-12-08 Created: 2016-11-28 Last updated: 2016-12-08Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • ieee
  • modern-language-association-8th-edition
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More styles
Language
  • de-DE
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  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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  • asciidoc
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