Comparison of Different Channel Estimation Techniques in OFDM Systems
Md Faran1, Pardeep Mor2

1Md. Faran, Department of ECE, Alfalah Engineering and Technology, Faridabad (Haryana), India.
2Mr. Pardeep Mor, Department of ECE, Alfalah Engineering and Technology, Faridabad (Haryana), India.
Manuscript received on 10 September 2013 | Revised Manuscript received on 19 September 2013 | Manuscript Published on 30 September 2013 | PP: 30-32 | Volume-3 Issue-4, September 2013 | Retrieval Number: D1168093413/13©BEIESP
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Abstract: The present work addresses channel estimation based on the Minimum Mean Square Error (MMSE) and Least Square (LS) criteria and also considers time-domain channel statistics. It presents an optimal criterion for the pilots, and corresponding optimal designs enabling complexity reductions. Using a general model for a slowly fading channel, the MMSE and LS estimators and a method for modifications compromising between complexity and performance is presented. The symbol error rate for a 16-QAM system is estimated by means of simulation results. MMSE (minimum mean square error) and LS (least square) estimators are also examined. The MMSE estimator has good performance but high complexity. The LS estimator has low complexity, but its performance is not as good as that of the MMSE estimator. Comparison is done for both types of estimators for channel estimation and the results are observed, considering the performances of channel estimators according to their behavior to symbol error rate and mean square error. Therefore, SNR of different estimators is studied corresponding to the particular SER value. OFDM-based systems are generally used in time varying frequency selective fading channels. In order to achieve the potential advantages of OFDM based systems, the channel coefficients should be estimated with minimum error. Finally, it is concluded that modified estimators give better performance than the ordinary estimators in OFDM systems.
Keywords: (LS), 16 QAM, MMSE, OFDM.

Scope of the Article: Expert Systems