Carrier frequency offset estimation based on data-dependent superimposed training for OFDM systems

Abstract

In this paper, we propose a solution to the carrier frequency offset (CFO) estimation based on data dependent superimposed training scheme for Orthogonal Frequency Division Multiplexing (OFDM) systems. The proposed CFO estimation can improve the bandwidth efficiency compared with traditional pilot assistant scheme because it consumes no extra bandwidth for the training sequence is superimposed to the data sequence. The simulations demonstrate that the proposed estimator can approach the performance of the pilot assistant scheme very well in terms of MSE and BER with great bandwidth efficiency improvement. Overall, the proposed solution outperforms the traditional pilot assistant scheme.