Radio environment map based maximum a posteriori Doppler shift estimation for LTE-R

Due to the high speed of the HSTs (high speed trains), Doppler shift estimation is a big challenge for OFDM (Orthogonal Frequency Division Multiplexing) based LTE-R (LTE based communication systems for high speed Rail), which is very sensitive to Doppler shifts. Exploiting the unique feature of HSTs, i.e. they move along a given railway, resulting in a regular, repetitive and predictable Doppler shift curve, a REM (radio environment map) including the Doppler shift information can be constructed via field tests. Using the Doppler estimation from REM as a priori knowledge, a MAPE (maximum a posteriori estimator) is proposed to improve the estimation performance. The CRLB (Cramer-Rao lower bound) is derived for the MAPE and provides interesting insights. The performance of MAPE is evaluated and compared to that of classical CPE (cyclic-prefix based estimator) and REME (REM estimation) by simulations. It is shown that combining the advantages of CPE and REME, MAPE could always outperform either CPE or REME. Moreover, MAPE is robust to the location error, which is one of the main error sources and limits the performance of REME.