Delay-Doppler Channel Estimation by Leveraging the Ambiguity Function in OFDM Systems

This paper proposes a new channel estimation method for orthogonal frequency division multiplexing (OFDM) systems in high-mobility multipath channels based on the delay-Doppler deterministic channel model. The proposed method identifies the system's delay-Doppler path coordinates before linear regression is used to determine the path components. An iterative path coordinate identification approach using the multiple signal classification (MUSIC) algorithm is proposed. This approach uses existing pilot offsets and inter-path influence (IPI) cancellation to improve the accuracy of the channel estimation. The IPI cancellation algorithm provides significant improvements over the symplectic finite Fourier transform (SFFT) algorithm. In addition, by leveraging the ambiguity function, the proposed inter-carrier interference (ICI) compensation method significantly improves the accuracy of channel estimation in challenging high-noise regimes and high-mobility environments. We show that the normalised mean squared error (NMSE) of the estimated channel is reduced by two to three orders of magnitude at a signal-to-noise ratio (SNR) of 5 and 45 dB, respectively, compared to a minimum mean squared error (MMSE)-based interpolation method.