To solve the pilot pollution problem caused by noise interference in orthogonal frequency division multiplexing(OFDM)systems,a deep learning based channel estimation model called CE-SERNet was designed.The least square channel estimate at the pilot position was regarded as a low resolution image with noise,which was taken as the network input,and the attention mechanism and residual network were used to de-noise and restore the high resolution image,the channel estimation of OFDM system was realized.Simulation results show that the proposed network is superior to the existing deep learning-based methods at both low and high pilot conditions.Compared with traditional LS and MMSE algorithms,it has significant improve-ments in estimation accuracy and strong robustness in different channel scenarios.
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