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http://dx.doi.org/10.3837/tiis.2016.09.012

Iterative Channel Estimation for MIMO-OFDM System in Fast Time-Varying Channels  

Yang, Lihua (Jiangsu Key Laboratory of Wireless Communication, Nanjing University of Posts and Telecommunications)
Yang, Longxiang (Jiangsu Key Laboratory of Wireless Communication, Nanjing University of Posts and Telecommunications)
Liang, Yan (Jiangsu Key Laboratory of Wireless Communication, Nanjing University of Posts and Telecommunications)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.10, no.9, 2016 , pp. 4240-4258 More about this Journal
Abstract
A practical iterative channel estimation technique is proposed for the multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system in the high-speed mobile environment, such as high speed railway scenario. In the iterative algorithm, the Kalman filter and data detection are jointed to estimate the time-varying channel, where the detection error is considered as part of the noise in the Kalman recursion in each iteration to reduce the effect of the detection error propagation. Moreover, the employed Kalman filter is from the canonical state space model, which does not include the parameters of the autoregressive (AR) model, so the proposed method does not need to estimate the parameters of AR model, whose accuracy affects the convergence speed. Simulation results show that the proposed method is robust to the fast time-varying channel, and it can obtain more gains compared with the available methods.
Keywords
MIMO-OFDM; high-speed mobile; fast time-varying channel; iterative channel estimation; Kalman filter; data detection error;
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