Carrier Frequency Offset Estimation of FTN Signaling Based on Adaptive Kalman Filter

Abstract

Faster-than-Nyquist (FTN) technology improves the transmission efficiency and spectrum efficiency of the system. However, the infinite length of intersymbol interference (ISI) introduced by FTN technology not only challenges the equalization of FTN signaling (FTNS), but also makes it difficult to synchronize the FTNS. Traditional carrier frequency offset (CFO) estimation methods will deteriorate in terms of threshold and accuracy. In order to overcome this difficulty, we propose an adaptive Kalman filter to further estimate the CFO of the FTNS after blind estimation using the traditional algorithm. Compared with the estimation without Kalman filter, the estimation after Kalman filter is more stable and accurate. And the adaptive Kalman filter has better performance in both anti-outliers and dynamic performance of the system, compared with Kalman filter.