Deblurring based 2D Channel Estimation and Equalization In ZP-OTFS Systems

Orthogonal Time Frequency Space (OTFS) modulation is emerging as a new waveform candidate that is capable of handling Dopplers in wireless communication systems. Zero Padded-OTFS (ZP-OTFS) is a variant of the OTFS system that efficiently deals with ISI due to delay spread. Conventionally, performing channel estimation and equalization of ZP-OTFS signals in the time domain leads to higher computational complexity. In this work, a low complexity, channel estimation and equalization directly performed in the 2D domain using Weiner deconvolution has been proposed by considering the effect of wireless channel on received symbols in delay Doppler space is analogous to blurred images. The concept of oversampling has also been proposed to deal with fractional delay and fractional Doppler for improving the accuracy of channel estimation and improving the performance of channel equalization. The simulation performed over the Extended Vehicular A (EVA) channel confirmed that with an increase in Oversampling Ratio (OSR), better bit error rate performance is observed (BER). It has been observed that BER performance approaches AWGN performance at higher values of pilot power and higher oversampling ratio.