Frequency estimators for MIMO-OFDM systems

Orthogonal frequency division multiplexing (OFDM) systems are known to be sensitive to carrier frequency offset (CFO). This paper is concerned with the CFO estimation for multiple input multiple output (MIMO) systems employing OFDM waveforms. We present two approaches to derive maximum likelihood (ML) pilot-assisted frequency estimators that use either two or multiple identical training symbols. It is shown that the resulting ML frequency estimators are similar to maximum ratio combining versions of Moose estimator and Yu-Su solution, respectively. Numerical examples demonstrate that the proposed frequency estimators are robust against spatial Signal-to-noise ratio (SNR) variation and they yield performance superior to that of the corresponding single-antenna system.