Microwave Mobile Communications
Microwave Mobile Communications
Robust multiuser detection in non-Gaussian channels
IEEE Transactions on Signal Processing
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Subspace-based (semi-) blind channel estimation for block precodedspace-time OFDM
IEEE Transactions on Signal Processing
Optimal training for MIMO frequency-selective fading channels
IEEE Transactions on Wireless Communications
Space-time block codes from orthogonal designs
IEEE Transactions on Information Theory
A simple transmit diversity technique for wireless communications
IEEE Journal on Selected Areas in Communications
Channel estimation for OFDM systems with transmitter diversity in mobile wireless channels
IEEE Journal on Selected Areas in Communications
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The current channel estimation algorithm is often performed under the assumption that the additive channel noise is white and Gaussian, but there is experimental evidence to show that the additive channel noise is non-Gaussian and non-linear in a wireless environment. This paper addresses the MIMO-OFDM channel estimation based on particle filtering and under the Middleton Class A noise model. The proposed algorithm models the wireless fading channel as an AR process, and optimizes the particles distribution using a variable step-size gradient information. Compared with conventional estimation approaches, the proposed method outperforms in robust to non-Gauss distribution noise. The simulations show the effectiveness of the new scheme.