State-space estimation of rapidly-varying carrier frequency offsets in OFDM systems

The problem with the application of parametric algorithms to estimate rapidly varying carrier frequency offsets (CFO) in OFDM systems is that they are rather bandwidth-inefficient as a substantial part of the received signal is occupied with pilot symbols. Herein, we propose to minimize this drawback, i.e., we aim to increase the spacing between pilot symbols by using a truncated Taylor's series to predict the CFO, where the derivatives up to order d-l of the series terms are recursively estimated with a d-order Kalman-Bucy filter (KBF). For large prediction intervals simulations show that the bit error floors can be significantly reduced when the conventional linear non-recursive CFO predictor is replaced with a fourth-order KBF.