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When NOMA meets sparse signal processing : asymptotic performance analysis and optimal sequence design

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Qi, T., Feng, W., Chen, Yunfei and Wang, Y. (2017) When NOMA meets sparse signal processing : asymptotic performance analysis and optimal sequence design. IEEE Access, 5 . 18516 -18525. doi:10.1109/ACCESS.2017.2727518

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Official URL: http://doi.org/10.1109/ACCESS.2017.2727518

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Abstract

Due to limited radio resources, non-orthogonal multiple
access (NOMA) is a promising technology to enable massive
connectivity in future 5G and beyond wireless networks. However,
it suffers from the multiple access interference (MAI), which
usually requires a high detection complexity to mitigate. In this
paper, we consider NOMA with sparse multiple-access sequences,
so as to leverage the message passing algorithm (MPA) for lowcomplexity and high-reliability multiuser detection. The optimal
sparsity of spreading sequences is analyzed by minimizing the
average bit error rate (BER) in the asymptotic large-system limit.
Based on the analysis, the optimal sparse sequences that optimize
the performance of MPA detector are designed in a systematically
hierarchical way. The sparse structure is constructed given the
target girth. Then, the values of nonzero entries are determined
to maximize the minimum distance. The detection performance
of the designed sparse sequences is presented for both additive
white Gaussian noise (AWGN) and Rayleigh fading channels.
Simulation results show the superiority of the proposed design
in comparison with existing schemes.

Item Type: Journal Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science > Engineering
Library of Congress Subject Headings (LCSH): Cell phone systems -- Standards, Wireless sensor networks
Journal or Publication Title: IEEE Access
Publisher: IEEE
ISSN: 2169-3536
Official Date: 16 July 2017
Dates:
DateEvent
16 July 2017Published
3 July 2017Accepted
Volume: 5
Page Range: 18516 -18525
DOI: 10.1109/ACCESS.2017.2727518
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
Funder: Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Natural Science Foundation of China] (NSFC), China. Guo jia ke xue ji shu bu [Ministry of Science and Technology] (CMST)
Grant number: 61231011, 6113200 (NSFC), 2013CB329001 (CMST)

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