Publication Date


Document Type


First Advisor

Tahernezhadi, Mansour

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Electrical Engineering


Engineering; Electrical engineering; MIMO systems; Orthogonal frequency division multiplexing; Electrical engineering


Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO- OFDM) provides a significant performance gain compared to the single antenna systems by using diversity and multiplexing techniques. The availability of channel state information at the receiver determines the multiplexing and diversity gain of the MIMO OFDM systems. In this thesis work, analysis and comparison of different pilot aided channel estimation algorithms have been performed. The Alamouti Space Frequency Block coding (SFBC) is used to achieve diversity, whereas Maximum Likelihood (ML) detector is used to decode the spatially coded symbols.;The pilot aided channel estimation is performed for both MIMO and Single Input Single Output (SISO) OFDM systems using the Least Square (LS) and Minimum Mean Square Error (MMSE) channel estimation algorithms for the block type and comb type pilots. Matlab simulations have been performed for estimating the channel in different scenarios like Rayleigh fading and Stanford University Interim (SUI) channel models at various doppler frequencies. The performance of different channel estimators have been evaluated for a 2x2 and 1x1 system using the mean square error (MSE) and bit error rate (BER). The MMSE estimator performs better than LS estimator in terms of BER but is a little complex. At low doppler frequencies MMSE estimator using block type pilots performs better while at high doppler frequencies MMSE estimator using comb type pilots perfoms better. The SUI channel model performed better than the Rayleigh channel due to presence of line of sight (LOS). Hence, the comb type MMSE estimator in MIMO OFDM is optimal in fast fading scenarios.


Advisors: Mansour Tahernezhadi.||Committee members: Peng-Yung Woo; Donald Zinger.


64 pages




Northern Illinois University

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