Abstract
In this paper, the Discrete Wavelet Transform is proposed to reduce PAPR and channel estimation. This paper focused on the Selected Mapping (SLM) and Partial Transmit Sequence (PTS) techniques using Wavelet transforms instead of conventional Fast Fourier Transforms. Using wavelets the filters for stationary and non-stationary signals can also be constructed. Wavelet based systems provide better spectral efficiency because of non-cyclic prefix requirement, with narrow side lobes and exhibit improved BER performance. In this work, performance of DFT, DCT, and DWT is considered in time domain. Simulation results show that the PAPR has been reduced in a great manner by wavelet SLM and PTS techniques. Simulations also reveal that DWT based transform outperforms the conventional DFT and DCT based channel estimator.
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