Since the vehicular environment is highly mobile, the transmitted messages are affected by the wireless channel effect. This makes channel estimation one of the important tasks in Vehicle-To-Everything (V2X) communications. In this paper, we propose a novel Multiple Sequential Constraint Removal (MSCR) algorithm of channel estimation, dedicated to V2X communications. This method is performed on a vehicular doubly selective channel, where the communication system is based on the Orthogonal Frequency Division Multiplexing (OFDM) waveform, with a high order modulation (64-QAM). The proposed approach is compared to state-of-the-art Least square (LS), minimum mean square error (MMSE) estimators and the iterative Sequential Constraint Removal (SCR) algorithms. It shows that it achieves better performance, where we can get a small symbol error rate (SER) on highly mobile scenarios (Highway with non-line of the sight), with a latency time that meets with the V2X communication requirements. © 2020 IEEE.