Steady-state Kalman filtering for channel estimation in OFDM systems utilizing SNR

Maduranga Liyanage, Iwao Sasase

研究成果: Conference contribution

抄録

Kalman filters are effective channel estimators but they have the drawback of having heavy calculations when filtering needs to be done in each sample. In our paper we obtain the steady-state Kalman gain to estimate the channel state thus eliminating a larger portion of the calculation burden. Steady-state value is calculated by transforming the vector Kalman filtering in to scalar domain by exploiting the filter characteristics when pilot subcarriers are used for channel estimation. Kalman filters operate optimally in the steady-state condition. Therefore by avoiding the convergence period of the Kalman gain, the proposed scheme is able to perform better than the conventional method. Also, driving noise variance of the channel is difficult to obtain practical situations and accurate knowledge is important for the proper operation of the Kalman filter. Thus we extend our scheme to operate in the absence of the knowledge of driving noise variance by utilizing received Signal-to-Noise Ratio (SNR). Simulation results show considerable estimator performance gain can be obtained compared to the conventional Kalman filter.

本文言語English
ホスト出版物のタイトルProceedings - 2009 IEEE International Conference on Communications, ICC 2009
DOI
出版ステータスPublished - 2009 11 23
イベント2009 IEEE International Conference on Communications, ICC 2009 - Dresden, Germany
継続期間: 2009 6 142009 6 18

出版物シリーズ

名前IEEE International Conference on Communications
ISSN(印刷版)0536-1486

Other

Other2009 IEEE International Conference on Communications, ICC 2009
国/地域Germany
CityDresden
Period09/6/1409/6/18

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • 電子工学および電気工学

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