Frequency-Offset Estimation for MIMO and OFDM Systems Using Orthogonal Training Sequences

We propose a training-sequence-based frequency-offset estimator for a multiple transmit-and-receive antenna system in frequency-flat fading channels. The estimator is based on the maximum likelihood (ML) criterion and does not require channel information. To reduce the computational load, they propose to use special training sequences-the periodic orthogonal codes. Using these codes, we get a closed form estimator which requires much lower computational load (some additions and multiplications). For the high signal-to-noise ratio and small frequency offset, the proposed estimator achieves the performance of the optimal ML estimator, which locates the peak of the likelihood function. We also apply the proposed estimator to a multiple antenna system in frequency-selective channels and an orthogonal-frequency-division-multiplexing system. With theoretical analysis and simulations, we evaluate the performance of the proposed estimator