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ELM-Based Signal Detection Scheme of MIMO System Using Auto Encoder

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Neural Information Processing (ICONIP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10639))

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Abstract

Signal detection scheme is the key technology to the implementation of multiple-input multiple-output (MIMO) wireless communication system, while the spatial-multiplexing coded MIMO systems cause a severe design challenge for signal detection algorithms. Although many researches focus on searching the solution space for optimal solution based on more efficient searching algorithm, the signal detection of MIMO system does not regarded as a classification problem. In this paper, the detection problem is considered as a feature classification, and a novel signal detection scheme of MIMO system based on extreme learning machine auto encoder (ELM-AE) is proposed. The proposed algorithm can efficiently extract the features of input data by ELM-AE and classify these representations to corresponding groups rapidly by using extreme learning machine (ELM). This paper has constructed a theoretical model of the proposed signal detector for MIMO system and carried out simulations to evaluating its performance. Simulation results indicate that the proposed detector outperforms many traditional schemes and state-of-the-art algorithms.

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Acknowledgments

The authors would like to thank the anonymous reviewers for their constructive and insightful comments for further improving the quality of this work. The research work was partially supported by the National Natural Science Foundation of China under Grant (61263005, 61563009), New Century Talents Project of the Ministry of Education under Grant No. NCET-12-0657.

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Guizhou Institute of Technology, Guiyang, 550001, China

    Fei Long & Xin Yan

  2. College of Big Data and Information Engineering, Guizhou University, Guiyang, 550025, China

    Xin Yan

Authors
  1. Fei Long
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  2. Xin Yan
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Corresponding author

Correspondence to Xin Yan .

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Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Derong Liu

  2. Guangdong University of Technology, Guangzhou, China

    Shengli Xie

  3. South China University of Technology, Guangzhou, China

    Yuanqing Li

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Dongbin Zhao

  5. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

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Long, F., Yan, X. (2017). ELM-Based Signal Detection Scheme of MIMO System Using Auto Encoder. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10639. Springer, Cham. https://doi.org/10.1007/978-3-319-70136-3_53

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  • DOI: https://doi.org/10.1007/978-3-319-70136-3_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70135-6

  • Online ISBN: 978-3-319-70136-3

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