A Novel Blind Detection Algorithm Based on Spectrum Sharing and Coexistence for Machine-to-Machine Communication

ZHANG Yun; ZHOU Jing; LIU Rong; YU Shujuan; LI Binrui

doi:10.23919/cje.2021.00.244

Volume 32 Issue 5

Sep. 2023

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Article Navigation > Chinese Journal of Electronics > 2023 > 32(5): 1036-1049

ZHANG Yun, ZHOU Jing, LIU Rong, et al., “A Novel Blind Detection Algorithm Based on Spectrum Sharing and Coexistence for Machine-to-Machine Communication,” Chinese Journal of Electronics, vol. 32, no. 5, pp. 1036-1049, 2023, doi: 10.23919/cje.2021.00.244

Citation:

ZHANG Yun, ZHOU Jing, LIU Rong, et al., “A Novel Blind Detection Algorithm Based on Spectrum Sharing and Coexistence for Machine-to-Machine Communication,” Chinese Journal of Electronics, vol. 32, no. 5, pp. 1036-1049, 2023, doi: 10.23919/cje.2021.00.244

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A Novel Blind Detection Algorithm Based on Spectrum Sharing and Coexistence for Machine-to-Machine Communication

doi: 10.23919/cje.2021.00.244

ZHANG Yun^{1, 2
,},
ZHOU Jing^{1, 2
,},
LIU Rong^{1, 2
,},
YU Shujuan^{1, 2
,},
LI Binrui^{1, 2
,}

1.
College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
2.
College of Flexible Electronics (Future Technology), Nanjing University of Posts and Telecommunications, Nanjing 210023, China

Funds: This work was supported by the National Natural Science Foundation of China (61977039).

More Information

Author Bio:
Yun ZHANG was born in Nanjing, Jiangshu Province, China, in 1977. She received the M.S. and Ph.D. degrees from Nanjing University of Posts and Telecommunication, Nanjing, China, in 2005 and 2011 respectively. She has been a lectorate with the college of Electrical Science and Engineering, Nanjing University of Posts and Telecommunication since 2012. Her research interests are in the fields of adaptive signal processing, blind channel equalization, and digital wireless communications. (Email: y021001@njupt.edu.cn)

Jing ZHOU was born in Changzhou, Jiangsu Province, China, in 1998. She is a master student of Nanjing University of Posts and Telecommunications. Her research directions are intelligent signal processing and communication signal processing. (Email: Z_Jing1020@163.com)

Rong LIU was born in Nantong, Jiangsu Province, China, in 1999. He is a master student of Nanjing University of Posts and Telecommunications. His research directions are intelligent signal processing and communication signal processing. (Email: 1021020927@njupt.edu.cn)

Shujuan YU was born in Hailar, Inner Mongolia, China, in 1967. She received the B.E. and M.S. degrees from Harbin Institute of Technology, Harbin, China, in 1989 and Southeast University, Nanjing, China, in 1995 respectively. She has been an Associate Professor and Master Tutor at College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications since 2007. (Email: yusj@njupt.edu.cn)

Binrui LI was born in Anyang, Henan Province, China, in 1997. She received the M.S. degree in Nanjing University of Posts and Telecommunications. Her research directions are intelligent signal processing, wireless sensor network, and communication signal processing. (Email: 1419866124@njupt.edu.cn)
Received Date: 2021-07-24
Accepted Date: 2023-02-14

Available Online: 2023-05-31

Publish Date: 2023-09-05

Abstract

Abstract

This paper proposes a new scheme that allows decentralized machine-to-machine (M2M) communication to share spectrum with conventional user communication in an orthogonal frequency division multiplexing system. This scheme can effectively separate and recover mixed signals at the receiving end. It mainly uses the signal space cancellation-complex system Hopfield neural network (SSC-CSHNN) blind detection algorithm to reconstruct the complementary projection operator and the blind detection performance function to restore the M2M communication signals. In order to further improve the anti-interference performance of the system and accelerate the convergence of the algorithm, the double sigmoid idea is introduced, and the signal space cancellation-double sigmoid complex system Hopfield neural network (SSC-DSCSHNN) blind detection algorithm is proposed. The proposed blind detection algorithm improves the anti-interference ability and the convergence speed and prevents the Hopfield neural network from falling into the local optimal solution based on the successful separation and recovery of mixed signals. Compared with existing methods, the blind detection algorithm used in this paper can directly detect the transmitted signal without identifying the channel.
- Machine-to-machine communication,
- 5G,
- Spectrum sharing,
- Signal space cancellation,
- Complex Hopfield neural network,
- Blind detection

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References(27)

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