Comparison of different channel estimation algorithms from ITS perspective

The channel estimation is an important issue for safety and non safety applications of intelligent transportation systems (ITS). Communication would come to a standstill if there were no channel estimation. It is essential to know the channel characteristics before sending a signal so that we have a fair knowledge of how distorted our received signal could be. Hence proper estimation is a major requirement to avoid erroneous reception. In this work, channel estimation algorithms, viz., LMS, RLS, MMSE and Kalman filter, are compared from ITS perspective. Further a case study, on OFDM based system in a utopian transport scenario, is presented to evaluate the efficiency of these algorithms. The simulation is carried out in MATLAB/ SIMULINK platform.