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Blind Signal Classif < roman > i </roman > cation for Non-Orthogonal Multiple Access in Vehicular Networks

Authors
Choi, MinseokYoon, DaejungKim, Joongheon
Issue Date
Oct-2019
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
NOMA; Silicon carbide; Modulation; Receivers; Interference cancellation; Multiplexing; Non-orthogonal multiple access (NOMA); blind signal classification; signaling overhead; spectrum efficiency; 5G-enabled vehicular networks
Citation
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, v.68, no.10, pp.9722 - 9734
Indexed
SCIE
SCOPUS
Journal Title
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume
68
Number
10
Start Page
9722
End Page
9734
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/62609
DOI
10.1109/TVT.2019.2932407
ISSN
0018-9545
Abstract
In this paper, blind signal classification and detection in a non-orthogonal multiple access (NOMA) system are explored. Since a NOMA scheme superposes the multiple-user signals within nonorthogonal resources, classical modulation classification methods used in orthogonal multiple access (OMA) systems are not sufficient to process the superposed NOMA signal. NOMA receivers require information about the multiple access schemes such as modulation order and need interference cancellation of the co-scheduled users signal; therefore, a NOMA system causes more high-layer signaling overheads than OMA during packet scheduling. Blind detection algorithms used for multiplexing information are considered to be possible solutions; however, they pose various challenges and could cause performance loss while performing blind modulation classification in the order of OMA/NOMA classification, co-scheduled users modulation classification, and classification of the signal, due to the necessity for successive interference cancellation. To improve the performance of blind detection, we propose a NOMA transmission scheme that applies phase rotation to data or pilot symbols depending on the NOMA multiplexing format, as an aid to the blind detection. The proposed classification algorithm can implicitly provide essential information on NOMA multiplexing without the need for any extra high layer signaling or resources. The performance improvement is verified through simulation studies, and it is found that the proposed algorithm provides a gain of more than 1dB compared to the existing blind signal classification methods and shows almost equivalent performance as the genie information scheme.
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