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Complexity Analysis of Massive MIMO Signal Detection Algorithms Based on Factor Graph

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5G for Future Wireless Networks (5GWN 2017)

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Abstract

Massive MIMO technology is one of the most promising concepts in 5G wireless system. In the uplink of a massive MIMO system, complexity and performance of signal detection are two key issues been concerned simultaneously. Many message passing algorithms based on factor graph have claimed to achieve nearly optimal performance at low complexity. A unified factor graph model is introduced to describe two typical message passing algorithm,approximate message passing (AMP) and message passing detection (MPD). By analyzing different message calculation methods in the two algorithms, their computational complexity and performance are given in detail. Simulation results have shown that MPD exceeds AMP in both complexity and performance.

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References

  1. Larsson, E., Edfors, O., Tufvesson, F.: Massive MIMO for next generation wireless systems. IEEE Commun. Mag. 52(2), 186–195 (2013)

    Article  Google Scholar 

  2. Som, P., Datta, T., Srinidhi, N., Chockalingam, A.: Low-complexity detection in large-dimension MIMO-ISI channels using graphical models. IEEE J. Sel. Top. Sig. Process. 5(8), 1497–1511 (2011)

    Article  Google Scholar 

  3. Wu, S., Kuang, L., Ni, Z., Lu, J., Huang, D., Guo, Q.: Low-complexity iterative detection for large-scale multiuser MIMO-OFDM systems using approximate message passing. IEEE J. Sel. Top. Sig. Process. 8(5), 902–915 (2014)

    Article  Google Scholar 

  4. Narasimhan, T.L., Chockalingam, A.: Channel hardening-exploiting message passing (CHEMP) receiver in large-scale MIMO systems. IEEE J. Sel. Top. Sig. Process 8(5), 847–860 (2013)

    Article  Google Scholar 

  5. Guo, R., Li, X., Fu, W., Hei, Y.: Low-complexity signal detection based on relaxation iteration method in massive MIMO systems. Commun. China 12(Supplement), 1–8 (2015)

    Article  Google Scholar 

  6. Hochwald, B.M., Marzetta, T.L., Tarokh, V.: Multiple-antenna channel hardening and its implications for rate feedback and scheduling. IEEE Trans. Inf. Theory 50(9), 1893–1909 (1909)

    Article  MathSciNet  MATH  Google Scholar 

  7. Pretti, M.: A message-passing algorithm with damping. J. Stat. Mech. Theory Exp. 2005(11), 283–292 (2005)

    Article  Google Scholar 

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Acknowledgement

This paper is supported by the National Natural Science Foundation of China (No. 61171099 & No. 61671080).

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Authors and Affiliations

  1. Key Lab of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China

    Zhichao Yao, Chao Dong, Kai Niu & Zhiqiang He

Authors
  1. Zhichao Yao
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  2. Chao Dong
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  3. Kai Niu
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  4. Zhiqiang He
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Corresponding author

Correspondence to Zhichao Yao .

Editor information

Editors and Affiliations

  1. University of Science and Technology, Beijing, China

    Keping Long

  2. The University of British Columbia, Vancouver, British Columbia, Canada

    Victor C.M. Leung

  3. University of Science and Technology, Beijing, China

    Haijun Zhang

  4. Beijing University of Posts and Telecommunications, Beijing, China

    Zhiyong Feng

  5. Centre of Excellence in Telecommunications, The University of Sydney , Maze Crescent, Australia

    Yonghui Li

  6. University of Science and Technology, Beijing, China

    Zhongshan Zhang

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Yao, Z., Dong, C., Niu, K., He, Z. (2018). Complexity Analysis of Massive MIMO Signal Detection Algorithms Based on Factor Graph. In: Long, K., Leung, V., Zhang, H., Feng, Z., Li, Y., Zhang, Z. (eds) 5G for Future Wireless Networks. 5GWN 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 211. Springer, Cham. https://doi.org/10.1007/978-3-319-72823-0_24

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  • DOI: https://doi.org/10.1007/978-3-319-72823-0_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-72822-3

  • Online ISBN: 978-3-319-72823-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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