Performance enhancement of MIMO detectors using wavelet de-noising filters

  • Authors

    • Reham Wgeeh Electronics and Electrical Communications Department, Faculty of Engineering, Tanta University, Tanta Egypt
    • Amr Hussein Electronics and Electrical Communications Department, Faculty of Engineering, Tanta University, Tanta Egypt
    • Mahmoud Attia Electronics and Electrical Communications Department, Faculty of Engineering, Tanta University, Tanta Egypt
    2016-11-19
    https://doi.org/10.14419/ijet.v5i4.6371
  • Multiple Input- Multiple Output, Maximum Likelihood, Zero Forcing, Minimum Mean Square Error Detector, Wavelet De-n oising.

  • Abstract

    Multiple-Input Multiple-Output (MIMO) technology has attracted great attention in many wireless communication systems. It provides significant enhancement in the spectral efficiency, throughput, and link reliability. There are numerous MIMO signal detection techniques that have been studied in the previous decades such as Maximum Likelihood (ML), Zero Forcing (ZF), Minimum Mean Square Error (MMSE) detectors, etc. It is well known that the additive and multiplicative noise in the information signal can significantly degrade the performance of MIMO detectors. During the last few years, the noise problem has been the focus of much research, and its solution could lead to profound improvements in symbol error rate performance of the MIMO detectors. In this paper, ML, ZF, and MMSE based wavelet de-noising detectors are proposed. In these techniques, the noise contaminated signals from each receiving antenna element are de-noised individually in parallel to boost the SNR of each branch. The de-noised signals are applied directly to the desired signal detector. The simulation results revealed that the proposed detectors constructed on de-noising basis achieve better symbol error rate (SER) performance than that of systems currently in use.

  • References

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  • How to Cite

    Wgeeh, R., Hussein, A., & Attia, M. (2016). Performance enhancement of MIMO detectors using wavelet de-noising filters. International Journal of Engineering & Technology, 5(4), 131-134. https://doi.org/10.14419/ijet.v5i4.6371

    Received date: 2016-06-17

    Accepted date: 2016-08-25

    Published date: 2016-11-19