On the Pilot-Aided Channel Estimation for Windowed OTFS with Data Interference in Rapidly Time-Varying Channels

The orthogonal time-frequency space (OTFS) modulation is an effective technique to deal with the high-mobility challenge in vehicular wireless communications, whose data detection depends heavily on accurate channel estimation (CE). In pilot-aided CE, reducing guard symbols can achieve higher spectral efficiency. However, data interference is inevitable, especially in fractional Doppler channels. Therefore, this paper investigates the impact of data interference on CE, and aims to mitigate such data interference by adding a non-rectangular window in the time-frequency (TF) domain. To fulfill this goal, a Cramer-Rao lower bound (CRLB) is derived by considering the presence of data interference and a non-rectangular window for CE in OTFS. Different from the existing CRLB analysis for embedded-pilot OTFS, data interference is considered and treated as noise interference, resulting in a tighter derived CRLB that effectively reflects the impact of data interference on CE. By minimizing the derived CRLB with the rectangular window, a new pilot sequence is obtained, which can achieve lower CRLB and better BER performance compared to the Zadoff-Chu (ZC) sequence. On the other hand, windowing can loosen the CRLB due to its ability to suppress data interference. Under the same main lobe width, it is found that the Kaiser window and Slepian window are more effective in reducing data interference than Dolph-Chebyshev (DC) window and rectangular window. Our simulation results indicate that the interference from data to the pilot can be significantly reduced by employing appropriate windowing techniques, and the windowing functions employed play an important role in pilot-aided CE.