Comparative Analysis of Least Square, Minimum Mean Square Error and KALMAN Estimator Using DWT (Discrete Wavelet Transform)-Based MIMO-OFDM System

  • Neha AwasthiEmail author
  • Sukesha Sharma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 989)


This paper includes the BER performance of least square, minimum mean square estimator and KALMAN filter is evaluated. Wireless channel experience the ill effect of multipath propagation, signal fading, tracking of channel, and distortion of the transmitted signal using channel estimation technique. DWT-based MIMO-OFDM system is implemented and channel estimation is done using LS, MMSE, and KALMAN filter. Channel estimation employed to recover the transmitted data. The method was tested by MATLAB simulation and completion was scrutinized with distinct modulations like BPSK (binary phase shift keying), QAM (quadrature amplitude modulation), PSK (phase shift keying) and QPSK (quadrature phase shift keying) of least square, KALMAN filter, and minimum mean square estimator.


Channel estimation MIMO (multiple input multiple output) OFDM (orthogonal frequency division multiplexing) Pilot insertion Least square Minimum mean square estimator KALMAN filter BER DWT QAM PSK BPSK and QPSK 


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© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.UIET, Panjab UniversityChandigarhIndia

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