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

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3 Author(s)
Xianhua Dai ; Sch. of Electr. & Commun. Eng., Sun Yat-Sen Univ., Guangzhou, China ; Han Zhang ; Dong Li

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 lower-bound 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 training schemes.

Published in:

Communications, IEEE Transactions on  (Volume:58 ,  Issue: 2 )