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  • Artificial neural network based sparse channel estimation for OFDM systems 

    Authors:Tahir, Abdur Rehman Bin
    Publisher and Date:(Kadir Has University, 2017)
    In order to increase the communication quality in frequency selective fading channel environment, orthogonal frequency division multiplexing (OFDM) systems are used to combat inter-symbol-interference (ISI). In this thesis, a channel estimation scheme for the OFDM system in the presence of sparse multipath channel is studied. The channel estimation is done by using the artificial neural networks (ANNs) with Resilient Backpropagation training algorithm. This technique uses the learning capability ...

  • Data-Aided Autoregressive Sparse Channel Tracking for OFDM Systems 

    In order to meet future communication system requirements channel estimation over fast fading and frequency selective channels is crucial. In this paper Space Alternated Generalized Expectation Maximization Maximum a Posteriori (SAGE-MAP) based channel estimation algorithm is proposed for Orthogonal Frequency Division Multiplexing (OFDM) systems for Autoregressive (AR) modeled time-varying sparse channels. Also an initialization algorithm has been developed from the widely used sparse approximation ...