Linearly time-varying channel estimation for MIMO/OFDM systems using superimposed training

Authors:
Xianhua Dai;Han Zhang;Dong Li
Affiliations:
School of Electrical and Communication Engineering, Sun Yat-Sen University, Guangzhou, P. R. China;school of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, P. R. China and School of Electrical and Communication Engineering, Sun Yat-Sen University, Guangzhou ...;School of Electrical and Communication Engineering, Sun Yat-Sen University, Guangzhou, P. R. China
Venue:
IEEE Transactions on Communications
Year:
2010

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Abstract

Channel estimation for multiple-input multiple-output/orthogonal frequency-division multiplexing (MIMO/OFDM) systems in linearly time-varying (LTV) wireless channels using superimposed training (ST) is considered. The LTV channel is modeled by truncated discrete Fourier bases. Based on this model, a two-step approach is adopted to estimate the LTV channel over multiple OFDM symbols. We also present a performance analysis of the channel estimation and derive a closed-form expression for the channel estimation variances. It is shown that the estimation variances, unlike that of the conventional ST-based schemes, approach to a fixed lowerbound as the training length increases, which is directly proportional to information-pilot power ratios. To further enhance the channel estimation performance with a limited pilot power, an interference cancellation procedure is introduced to iteratively mitigate the information sequence interference to channel estimation. Simulation results show that the proposed algorithm outperforms frequency-division multiplexed trainings schemes.