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A method of channel estimation based on training sequences is proposed for MIMO-OFDM systems. Moreover, the criterion is derived by simplified means for optimum training sequences construction. Based on the criterion, two methods are proposed for construction of optimum training sequences. Computer simulations are conducted to evaluate the channel estimation and optimum training sequences construction...
In this paper, a simple subspace based semi-blind channel estimator is developed for precoded OFDM systems. This channel estimator relies on redundant linear preceding. With this proposed channel estimator, the channel identifiability is guaranteed up to one scalar ambiguity, regardless of the channel zero locations and the underlying signal constellations. The ambiguity can be resolved with the known...
MIMO-OFDM is a promising technique for broadband communications over mobile wireless channel. In this paper, we investigate the channel estimation problem for MIMO-OFDM systems. We proposed a novel EM (expectation maximization)-based channel estimation method. This proposed method employs the poly-nomial channel model along with the EM-based algorithm and makes a tradeoff between the computational...
MIMO-OFDM is a promising technique for broadband communications over mobile wireless channel. In this paper, we investigate the channel estimation problem for MIMO-OFDM systems. We proposed an EM-based method to implement channel estimation, in which the polynomial channel model was used. The proposed EM-based method partition the problem of estimating a multi-input channel into independent channel...
MIMO-OFDM is a promising technique for broadband communications over mobile wireless channel. In this paper, we investigate the channel estimation problem for MIMO-OFDM systems. We proposed an EM-based framework to implement parameters estimation of channels described by various models. Since EM-based algorithm avoids the matrix inversion encountered in other channel estimation methods, it is of great...
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