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

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Abstract

We address the problem of estimating the linearly time-varying (LTV) channel of orthogonal frequency division multiplexing (OFDM)/multiple-input multiple-output (MIMO) systems using superimposed training (ST). 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 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. For wireless communication systems with a limited transmission power, we optimize the ST power allocation by maximizing the lower bound of the average channel capacity. Simulation results show that the proposed approach outperforms the frequency-division multiplexed training schemes.

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Authors and Affiliations

  1. School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, 510006, China

    Han Zhang & DaRu Pan

  2. Department of Information Science and Technology, SUN Yat-sen University, Guangzhou, 510026, China

    XianHua Dai

Authors
  1. Han Zhang
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  2. XianHua Dai
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  3. DaRu Pan
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Correspondence to Han Zhang.

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Zhang, H., Dai, X. & Pan, D. Linearly time-varying channel estimation and training power allocation for OFDM/MIMO systems using superimposed training. Sci. China Inf. Sci. 54, 1456–1470 (2011). https://doi.org/10.1007/s11432-011-4241-8

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  • DOI: https://doi.org/10.1007/s11432-011-4241-8

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