BibTeX:

@article{IJIRSTV1I8003,
     title={A Comparative Analysis of LS and MMSE Channel Estimation Techniques for MIMO-OFDM System},
     author={Akash Kumar Shrivas},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={1},
     number={8},
     pages={44--48},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV1I8003.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

The objective of this study is up channel estimation accuracy in OFDM system as a result of channel state info is needed for detection at receiver and its accuracy affects the performance of system and it's essential to improve the channel estimation for a lot of reliable communications. OFDM system was chosen during this study because it's been wide used nowadays owing to its high knowledge rate, data rate and its adequate performance in frequency selective attenuation channels. The pilots were inserted among subcarriers in transmitter with distances emerged of sampling theory then Least sq. (LS) technique & minimum mean-square error (MMSE) was chosen for initial channel estimation in pilots at receiver, mistreatment applicable projected receiver, that has straight forward and usable structure, then channel state info was calculable by linear interpolator in information subcarriers, that uses 2 adjacent channel estimation in pilots to calculate channel in another subcarriers and associate degree LMS repetitive algorithmic rule, as well as a feedback of output is another to system. This algorithmic rule uses the channel estimation of last iteration in current estimation. Adding a LMS repetitive algorithmic rule to system, improves the channel estimation performance. Simulation results established the acceptable BER performance of repetitive channel estimation algorithm, that is closed to the best channel. The low complexity projected receiver as well as LMS algorithmic rule, has a higher potency than typical methods (without channel estimation & LMMSE ) and it will add lower quantity of SNRs.

Least Square (LS), Minimum Mean-Square Error (MMSE). OFDM, LS Channel Estimation, LMMSE Channel Estimation.