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Channel Estimation in OFDM Systems Using a Controlled Superimposition of Training Sequences

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Abstract

This work pertains to the use of superimposed training (ST) for channel estimation in orthogonal frequency division multiplexing (OFDM) based systems. A time domain coherent averaging based channel estimator is derived from the least squares criterion. By exploiting the periodicity of the training sequences in the time domain and inserting zeros instead of data at some of the training sequence subcarrier locations depending on the desired estimation accuracy, a controlled superimposition technique is proposed. This method includes the flexibility to trade off between bandwidth efficiency and performance. The mean squared estimation error (MSEE) performance of such a system is mathematically analyzed and a training sequence selection criterion optimizing the same is proposed. The simulation performance of the scheme is presented in terms of the MSEE and the bit error rate (BER) of the OFDM system. Such a scheme is attractive in high data rate scenarios in closed loop OFDM systems.

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Authors and Affiliations

  1. Networks Lab, G.S. Sanyal School of Telecommunications, IIT Kharagpur, Kharagpur, 721302, India

    Jinesh P. Nair

  2. Dept. of Electronics and Electrical Communication, IIT Kharagpur, Kharagpur, 721302, India

    Ratnam V. Raja Kumar

Authors
  1. Jinesh P. Nair
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  2. Ratnam V. Raja Kumar
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Correspondence to Jinesh P. Nair.

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Nair, J.P., Raja Kumar, R.V. Channel Estimation in OFDM Systems Using a Controlled Superimposition of Training Sequences. Circuits Syst Signal Process 29, 349–360 (2010). https://doi.org/10.1007/s00034-009-9139-y

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  • DOI: https://doi.org/10.1007/s00034-009-9139-y

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