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Yazar: Şen, Adnan × search.filters.applied.f.publicationcategory: Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı ×

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  • Küçük Resim
    Yayın
    Joint channel tracking and symbol detection for OFDM systems with Kalman filtering
    (Urban & Fischer Verlag, 2003) Şen, Adnan; Çırpan, Hakan Ali; Panayırcı, Erdal
    This paper proposes a new joint channel tracking and symbol detection scheme for pilot symbol-assisted OFDM systems in multipath fading. The proposed scheme uses Kalman filters for both channel tracking and subsequent equalization which are combined in the coupled estimator structure. Modelling the multipath fading channel as random processes to describe channel variations in a general AR framework lends itself to a state-space representation that enables the application of Kalman filtering for the tracking of channel variations. However, the proposed tracking algorithm requires knowledge of the transmitted symbols. This implies that an iterative method should be sought to obtain alternatively either channel or transmitted symbols. To compose the coupled estimator structure, a linear Kalman filter equalizer with the corresponding state-space model is therefore proposed for the detection of transmitted symbols. With the proposed Kalman filters, iterative structure is utilized to decode transmitted symbols and subsequently to track channel parameters. Finally, the performance of the proposed method is investigated through the experimental results.
  • Küçük Resim
    Yayın
    Adaptive Kalman receiver for OFDM systems with transmit diversity in mobile wireless channels
    (Walter De Gruyter GMBH, 2004-12) Şen, Adnan; Çırpan, Hakan Ali; Panayırcı, Erdal
    A new joint channel tracking and symbol detection scheme is proposed in this paper for pilot symbol assisted transmit diversity OFDM systems by exploiting the correlation of the adjacent subchannels. Modelling the channel frequency response of every subcarrier corresponding to each transmit antenna as random processes, we employ Kalman filters for both channel tracking and subsequent decoding with diversity gain. Among different stochastic models, the AR model is adopted herein for channel dynamics. Since the proposed adaptive receiver uses two Kalman filters to track the variations of the channel and subsequently to detect the information symbols, they are combined in the coupled receiver structure. Finally the performance of the proposed method is studied through experimental results.