  A novel intercarrier interference (ICI)-aware orthogonal frequency division
multiplexing (OFDM) channel estimation network ICINet is presented for rapidly
time-varying channels. ICINet consists of two components: a preprocessing deep
neural subnetwork (PreDNN) and a cascaded residual learning-based neural
subnetwork (CasResNet). By fully taking into account the impact of ICI, the
proposed PreDNN first refines the initial channel estimates in a
subcarrier-wise fashion. In addition, the CasResNet is designed to further
enhance the estimation accuracy. The proposed cascaded network is compatible
with any pilot patterns and robust against mismatched system configurations.
Simulation results verify the superiority of ICINet over existing networks in
terms of better performance and much less complexity.
