Neural Network Channel Estimation Based on Least Mean Error Algorithm in the OFDM Systems

  • Jun Sun
  • Dong-Feng Yuan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


We designed a new channel estimator including two parts of neural network to estimate the amplitude and the angle of the frequency domain channel coefficients, respectively. The least mean error (LSE) is used for training. This neural network channel estimator (NNCE) makes full use of the learning property of the neural network (NN). Once the NN was trained, it reflected the channel fading trait of the amplitude and the angle respectively. It was no need of any matrix computation and it can get any required accuracy. It has been validated that the estimator is available in the pilot-symbol-aided (PSA) OFDM system.


Channel Estimation Pilot Symbol Doppler Power OFDM System Frequency Channel Response 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jun Sun
    • 1
  • Dong-Feng Yuan
    • 1
    • 2
  1. 1.School of Information Science and EngineeringShandong UniversityJinanP.R. China
  2. 2.State Key Lab. on Mobile CommunicationsSoutheast UniversityNanjingP.R. China

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