Analysis on Wavelet Family based Channel Estimation for MIMO-OFDM System
A. Raja1, V. Thulasibai2
1A. Raja, Assistant Professor (SG), Department of Electronics and Communication Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, SIMATS Chennai (Tamil Nadu), India.
2Dr. V. ThulasiBai, Professor, Department of Electronics and Communication Engineering, KCG College of Technology, Chennai (Tamil Nadu), India.
Manuscript received on 14 November 2019 | Revised Manuscript received on 22 December 2019 | Manuscript Published on 31 December 2019 | PP: 622-624 | Volume-9 Issue-2S4 December 2019 | Retrieval Number: B12281292S419/2019©BEIESP | DOI: 10.35940/ijitee.B1228.1292S419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Channel estimation for (MIMO-OFDM) is an important part for present and future generation broadband wireless communications. OFDM, which uses for the spaced subcarriers to improving the performance. The channel estimation schemes based on pilot reduces the transmission rate and spectral efficiency. Many conventional schemes of channel estimation are not effective in reducing noise. It leads to poor quality signals at receiver at final stage. To rectify this problem, in this paper a wavelet family based channel estimation technique, is proposed and analyzed. The proposed research aims to estimate channels and reconstruct signal via wavelet transform, dyadic wavelet transform and fractional spline wavelet transform which enhances the spectrum efficiency and transmission rate. Simulation results shows that the fractional spline wavelet transform performs well for channel estimation and data signal reconstruction.
Keywords: Channel Estimation, Dyadic Wavelet Transform, Orthogonal Frequency Division Multiplexing (OFDM), Fractional Spline Wavelet Transform, Spectral Efficiency, Wavelet Transform.
Scope of the Article: Predictive Analysis