SCMA Decoding via Deep Learning

被引：22

作者：

Wei, Chia-Po ^{[1
]}

Yang, Han ^{[2
]}

Li, Chih-Peng ^{[2
]}

Chen, Yen-Ming ^{[2
]}

机构：

[1] Natl Sun Yat Sen Univ, Dept Elect Engn, Kaohsiung 804, Taiwan

[2] Natl Sun Yat Sen Univ, Inst Commun Engn, Kaohsiung 80424, Taiwan

来源：

IEEE WIRELESS COMMUNICATIONS LETTERS | 2021年 / 10卷 / 04期

关键词：

Neural networks; Bit error rate; Training data; Receivers; Fading channels; Downlink; NOMA; Sparse code multiple access (SCMA); deep neural network (DNN); bit error rate (BER); deep learning;

D O I：

10.1109/LWC.2020.3048068

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Sparse code multiple access (SCMA) has become a highly competitive technology for future cellular systems. For the receiver of the SCMA system, besides the traditional maximum likelihood and message passing algorithm solutions, a deep neural network (DNN) method that causes whirlwinds in image recognition can reduce the computational complexity of the decoder. We expect low complexity while maintaining a satisfactory bit error rate (BER) performance. As shown in our simulations, our proposed solution has better BER performance and lower computational complexity than other previously studied DNN solutions.

引用

页码：878 / 881

页数：4

共 19 条

[11] Power-Domain Non-Orthogonal Multiple Access (NOMA) in 5G Systems: Potentials and Challenges
Islam, S. M. Riazul
Avazov, Nurilla
Dobre, Octavia A.
Kwak, Kyung-Sup
[J]. IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2017, 19 (02): : 721 - 742
[12] Kang G.-M., 2017, P 2017 23 ASIA PACIF, P1
[13] Deep Learning-Aided SCMA
Kim, Minhoe
Kim, Nam-I
Lee, Woongsup
Cho, Dong-Ho
[J]. IEEE COMMUNICATIONS LETTERS, 2018, 22 (04) : 720 - 723
[14] A novel deep neural network based approach for sparse code multiple access
Lin, Jinzhi
Feng, Shengzhong
Yang, Zhile
Zhang, Yun
Zhang, Yong
[J]. NEUROCOMPUTING, 2020, 382 : 52 - 63
[15] Generalized Frequency Division Multiplexing for 5th Generation Cellular Networks
Michailow, Nicola
Matthe, Maximilian
Gaspar, Ivan Simoes
Caldevilla, Ainoa Navarro
Mendes, Luciano Leonel
Festag, Andreas
Fettweis, Gerhard
[J]. IEEE TRANSACTIONS ON COMMUNICATIONS, 2014, 62 (09) : 3045 - 3061
[16] Nilopour H, 2013, 2013 IEEE 24TH INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR, AND MOBILE RADIO COMMUNICATIONS (PIMRC), P332, DOI 10.1109/PIMRC.2013.6666156
[17] Design and Analysis of SCMA Codebook Based on Star-QAM Signaling Constellations
Yu, Lisu
Fan, Pingzhi
Cai, Donghong
Ma, Zheng
[J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2018, 67 (11) : 10543 - 10553
[18] Deep Learning in Mobile and Wireless Networking: A Survey
Zhang, Chaoyun
Patras, Paul
Haddadi, Hamed
[J]. IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2019, 21 (03): : 2224 - 2287
[19] Fast Automatic Vehicle Annotation for Urban Traffic Surveillance
Zhou, Yi
Liu, Li
Shao, Ling
Mellor, Matt
[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2018, 19 (06) : 1973 - 1984

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