On Limits of Wireless Communications in a Fading Environment when UsingMultiple Antennas
Wireless Personal Communications: An International Journal
Two-Dimensional Pilot-Symbol-Aided Channel Estimation by Wiener Filtering
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 3 - Volume 3
Wireless Communications
Blind and semi-blind channel identification methods using second order statistics for OFDM systems
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05
EM-based channel estimation algorithms for OFDM
EURASIP Journal on Applied Signal Processing
EM-Based Channel Estimation for MIMO OFDM System
NSWCTC '09 Proceedings of the 2009 International Conference on Networks Security, Wireless Communications and Trusted Computing - Volume 01
A comparison of pilot-aided channel estimation methods for OFDMsystems
IEEE Transactions on Signal Processing
Space-alternating generalized expectation-maximization algorithm
IEEE Transactions on Signal Processing
Totally blind channel estimation for OFDM on fast varying mobile radio channels
IEEE Transactions on Wireless Communications
Iterative interference cancellation and channel estimation for mobile OFDM
IEEE Transactions on Wireless Communications
Low-Complexity Map Channel Estimation for Mobile MIMO-OFDM Systems
IEEE Transactions on Wireless Communications
Space-time block codes from orthogonal designs
IEEE Transactions on Information Theory
IEEE Transactions on Consumer Electronics
A simple transmit diversity technique for wireless communications
IEEE Journal on Selected Areas in Communications
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In this paper, a novel semi-blind channel estimation and symbol detection based on space-alternating generalized expectation-maximization (SAGE) algorithm are proposed for space time block coded (STBC) multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems. At the receiver, the transmitted signals of all users are added. By utilization of SAGE algorithm, this superimposed received signals are decomposed into their signal components. Then, the channel is estimated at pilot positions. After that, the channel estimation in the other positions are obtained by interpolation and symbol detection is done by utilizing the estimated channel. In SAGE algorithm, selection of initial value is very important for the convergence. We discuss the appropriate range for selection of initial value in this paper. Simulation results show that by increasing the number of users, the slope of bit error rate curve increases with same initial value and the channel estimation becomes worse by increasing the iteration of SAGE algorithm if the initial value is not selected in the proposed rang.