ISSN 0253-2778

CN 34-1054/N

Open AccessOpen Access JUSTC

Two-dimensional DCT-based channel estimation for OFDMA systems

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  • Received Date: 30 May 2009
  • Rev Recd Date: 17 July 2009
  • Publish Date: 31 October 2009
  • In orthogonal frequency division multiple access (OFDMA) systems, multiple access is achieved by assigning some time-frequency resource blocks to individual users. In this case, the conventional discrete Fourier transform (DFT)-based channel estimator suffers from an irreducible error floor. On the other hand, the DFT-based filtering and/or interpolation in time-domain also have performance degradation for systems with high Doppler frequency. In order to solve these two problems, a two dimensional discrete cosine transform (2-D DCT)-based channel estimator for OFDMA systems is proposed. Simulation results show that the performance of the proposed estimator can well approach the 2-D linear minimum mean square error (LMMSE) channel estimation with low implementation complexity. Furthermore, the proposed estimator can provide high accuracy channel estimation even in the low signal-to-noise ratio region, which contributes to the implementation of green communications.
    In orthogonal frequency division multiple access (OFDMA) systems, multiple access is achieved by assigning some time-frequency resource blocks to individual users. In this case, the conventional discrete Fourier transform (DFT)-based channel estimator suffers from an irreducible error floor. On the other hand, the DFT-based filtering and/or interpolation in time-domain also have performance degradation for systems with high Doppler frequency. In order to solve these two problems, a two dimensional discrete cosine transform (2-D DCT)-based channel estimator for OFDMA systems is proposed. Simulation results show that the performance of the proposed estimator can well approach the 2-D linear minimum mean square error (LMMSE) channel estimation with low implementation complexity. Furthermore, the proposed estimator can provide high accuracy channel estimation even in the low signal-to-noise ratio region, which contributes to the implementation of green communications.
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