Eigenvalue decomposition based estimators of carrier frequency offset in multicarrier underwater acoustic communication

We propose computationally efficient carrier frequency offset estimators for multicarrier underwater acoustic communication using identical pilot tones equi-spaced in the frequency domain. The first estimator uses the phase of the maximal eigenvector of a channel-dependent correlation matrix. Next, the phase of the minimal eigenvector of a channel-independent correlation matrix is combined with the first estimation using a weighted linear least squares principle. The third estimator solves a generalized eigenvalue decomposition problem by jointly considering the two correlation matrices, and then performs a similar second step as the previous estimator. Simulations and pool trials show that the proposed estimators achieve similar performance as common estimation techniques while surpassing them in severe environments.