Blind Maximum Likelihood Carrier Frequency Offset Estimation for OFDM With Multi-Antenna Receiver

In this paper, based on the maximum likelihood (ML) criterion, we propose a blind carrier frequency offset (CFO) estimation method for orthogonal frequency division multiplexing (OFDM) with multi-antenna receiver. We find that the blind ML solution in this situation is quite different from the case of single antenna receiver. As compared to the conventional MUSIC-like CFO searching algorithm, our proposed method not only has the advantage of being applicable to fully loaded systems, but also can achieve much better performance in the presence of null subcarriers. It is demonstrated that the proposed method also outperforms several existing estimators designed for multi-antenna receivers. The theoretical performance analysis and numerical results are provided, both of which demonstrate that the proposed method can achieve the Cramér-Rao bound (CRB) under the high signal-to-noise ratio (SNR) region.