A DNN-Based Channel Estimation Method for Spectral Efficient Frequency Division Multiplexing Systems

CHEN Jiarun; YU Baoxian; WANG Jianying; ZHANG Han

doi:10.6054/j.jscnun.2020038

Journal of South China Normal University (Natural Science Edition) > 2020 > 52(3): 17-21. > DOI: 10.6054/j.jscnun.2020038

CHEN Jiarun, YU Baoxian, WANG Jianying, ZHANG Han. A DNN-Based Channel Estimation Method for Spectral Efficient Frequency Division Multiplexing Systems[J]. Journal of South China Normal University (Natural Science Edition), 2020, 52(3): 17-21. DOI: 10.6054/j.jscnun.2020038

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A DNN-Based Channel Estimation Method for Spectral Efficient Frequency Division Multiplexing Systems

Guangdong Provincial R & D Center of Cardiovascular Individual Medicine & Big Data//School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou 510006, China

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Received Date: September 20, 2019
Available Online: March 21, 2021

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Abstract

A channel estimation method based on deep neural network (DNN) for spectral efficient frequency division multiplexing (SEFDM) systems is proposed. The method employs uniform spaced orthogonal pilot symbols to achieve the channel estimation. To be specific, the received pilot signals are used as the input of the four-layer DNN in order to extract the channel features. Simulation results show that the proposed scheme can yield a smaller mean square error (MSE) and, in turn, perform better demodulation in comparison with the conventional least square (LS) method. In particular, the DNN-based method is more robust to the number of pilots, which indicates its superiority.
- deep neural network,
- spectral efficient frequency division multiplexing,
- channel estimation

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