Adaptive Joint Semi-blind Estimation of CFO and Channel for OFDM Systems

Abstract

The large number of subcarriers, used in OFDM systems, increases the sensivity to frequency offset which results from a Doppler shift, due to mobile movement, as well as from a mismatch between the carrier frequencies at the transmitter and receiver. The problem of channel estimation in a practical OFDM receiver that suffers from CFO has been addressed in this paper. We first derived the modified MUSIC based blind CFO estimator. Next, we propose new joint training-based and joint semi-blind CFO and channel estimation for OFDM systems. Whereas the training-based estimator only assumes knowledge of pilot tones, the semi-blind estimator assumes knowledge of the virtual subcarriers (VSCs). For both estimators we derive a maximum likelihood (ML) algorithm for block processing and LMS algorithm for adaptive processing. It is demonstrated that the CFO estimators are able to perform well with a very small number of OFDM blocks. The performance of our estimators was investigated by simulations.