DFT-based channel estimation with symmetric extension for OFDMA systems

  • Authors:

  • Yi Wang;Lihua Li;Ping Zhang;Zemin Liu

  • Affiliations:

  • Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunication, Ministry of Education and Wireless Technology Innovation Institute, Beijing University of Po ...;Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunication, Ministry of Education and Wireless Technology Innovation Institute, Beijing University of Po ...;Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunication, Ministry of Education and Wireless Technology Innovation Institute, Beijing University of Po ...;Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunication, Ministry of Education and Wireless Technology Innovation Institute, Beijing University of Po ...

  • Venue:
  • EURASIP Journal on Wireless Communications and Networking - Special issue on OFDMA architectures, protocols, and applications
  • Year:
  • 2009

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Abstract

A novel partial frequency response channel estimator is proposed for OFDMA systems. First, the partial frequency response is obtained by least square (LS) method. The conventional discrete Fourier transform (DFT) method will eliminate the noise in time domain. However, after inverse discrete Fourier transform (IDFT) of partial frequency response, the channel impulse response will leak to all taps. As the leakage power and noise are mixed up, the conventional method will not only eliminate the noise, but also lose the useful leaked channel impulse response and result in mean square error (MSE) floor. In order to reduce MSE of the conventional DFT estimator, we have proposed the novel symmetric extension method to reduce the leakage power. The estimates of partial frequency response are extended symmetrically. After IDFT of the symmetric extended signal, the leakage power of channel impulse response is self-cancelled efficiently. Then, the noise power can be eliminated with very small leakage power loss. The computational complexity is very small, and the simulation results show that the accuracy of our estimator has increased significantly compared with the conventional DFT-based channel estimator.