Skip to main content
SpringerLink
Log in

Genetic-Algorithm-Driven MIMO Multi-user Detector for Wireless Communications

  • Conference paper
  • First Online:
Contemporary Complex Systems and Their Dependability (DepCoS-RELCOMEX 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 761))

Included in the following conference series:

  • 521 Accesses

Abstract

In the paper, evolutionary optimization strategy, represented by the genetic algorithm (GA) is considered as a multiuser detection (MUD) method for a multiple-input multiple-output (MIMO) wireless system. With the aim to boost lacking GA convergence, Zero-Forcing (ZF) detection is proposed as an initial processing phase. Additionally, a multi-stage GA routine is considered as a method to make the search for data estimates more effective.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Tse, D., Viswanath, P.: Fundamentals of Wireless Communication, 1st edn. Cambridge University Press, New York (2005)

    Google Scholar 

  2. Barry, J.R., Lee, E.A., Messerschmitt, D.G.: Digital Communication. Springer, Netherlands (2012)

    Google Scholar 

  3. Chen, M.: Iterative Detection for Overloaded Multiuser MIMO OFDM Systems. Dissertation, University of York (2013)

    Google Scholar 

  4. Berenguer, I.: Advanced Signal Processing Techniques for MIMO Communication Systems. Dissertation, University of Cambridge (2005)

    Google Scholar 

  5. Getu, A.: Genetic Algorithm-Based Joint Channel Estimation and Data Detection For Multi-User MIMO. Dissertation, Addis Ababa University (2014)

    Google Scholar 

  6. Sivanandam, S.N., Deepa, S.N.: Introduction to Genetic Algorithms, 1st edn. Springer-Verlag, New York (2008)

    Google Scholar 

  7. Coley, D.A.: An Introduction to Genetic Algorithms for Scientists and Engineers. World Scientific Publishing Co Inc., Massachusetts (1999)

    Google Scholar 

  8. Haupt, R.L., Haupt, S.E.: Practical Genetic Algorithms. John Wiley & Sons, Hoboken (2004)

    Google Scholar 

  9. Abramson, M.A.: Genetic Algorithm and Direct Search Toolbox User’s Guide. The MathWorks Inc., Massachusetts (2007)

    Google Scholar 

  10. Simon, D.: Evolutionary Optimization Algorithms. John Wiley & Sons, Hoboken (2013)

    Google Scholar 

  11. Chipperfield, A.J., Fleming, P.J., Pohlheim, H.: A genetic algorithm toolbox for MATLAB. In: Proceedings of the International Conference on Systems Engineering, 6–8 September, pp. 200–207. Coventry, UK (1994)

    Google Scholar 

Download references

Acknowledgment

The presented work has been funded by the Polish Ministry of Science and Higher Education within the status activity task “Wireless networks – multiple access, transmission, error protection” in 2018 (Grant No. 08/81/DSPB/8123).

Author information

Authors and Affiliations

  1. Faculty of Electronics and Telecommunications, Chair of Wireless Communications, Poznan University of Technology, 60-695, Poznań, Poland

    Mohammed Jasim Khafaji & Maciej Krasicki

Authors
  1. Mohammed Jasim Khafaji
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maciej Krasicki
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammed Jasim Khafaji .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Wojciech Zamojski

  2. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Jacek Mazurkiewicz

  3. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Jarosław Sugier

  4. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Tomasz Walkowiak

  5. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Janusz Kacprzyk

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Khafaji, M.J., Krasicki, M. (2019). Genetic-Algorithm-Driven MIMO Multi-user Detector for Wireless Communications. In: Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J. (eds) Contemporary Complex Systems and Their Dependability. DepCoS-RELCOMEX 2018. Advances in Intelligent Systems and Computing, vol 761. Springer, Cham. https://doi.org/10.1007/978-3-319-91446-6_25

Download citation

Publish with us

Policies and ethics

Search

Navigation