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SteadyState Kalman Filtering for Channel Estimation in OFDM Systems for Rayleigh Fading Channels
Maduranga LIYANAGE Iwao SASASE
Publication
IEICE TRANSACTIONS on Communications
Vol.E92B
No.7
pp.24522460 Publication Date: 2009/07/01
Online ISSN: 17451345
DOI: 10.1587/transcom.E92.B.2452
Print ISSN: 09168516 Type of Manuscript: PAPER Category: Wireless Communication Technologies Keyword: orthogonalfrequencydivisionmultiplexing (OFDM), channel estimation, steadystate, Kalman filter,
Full Text: PDF(288.7KB)>>
Summary:
Kalman filters are effective channel estimators but they have the drawback of having heavy calculations when filtering needs to be done in each sample for a large number of subcarriers. In our paper we obtain the steadystate Kalman gain to estimate the channel state by utilizing the characteristics of pilot subcarriers in OFDM, and thus a larger portion of the calculation burden can be eliminated. Steadystate value is calculated by transforming the vector Kalman filtering in to scalar domain by exploiting the filter charactertics when pilot subcarriers are used for channel estimation. Kalman filters operate optimally in the steadystate 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. Therefore, we extend our scheme to operate in the absence of the knowledge of driving noise variance by utilizing received SignaltoNoise Ratio (SNR). Simulation results show considerable estimator performance gain can be obtained compared to the conventional Kalman filter.

