ML-based joint estimation of frequency and sampling clock offsets for OFDM systems

In this paper, we present a joint algorithm to estimate the fine symbol timing and carrier frequency offsets of wireless orthogonal frequency division multiplexing (OFDM) signals. To jointly estimate synchronization parameters using the maximum likelihood (ML) criterion, we propose to transmit a special pilot symbol. By using a periodic training sequence, we convert the problem of obtaining the ML solution from searching exhaustively over the entire uncertainty range to that of solving a polynomial, thereby greatly reducing the computational load. With the proposed orthogonal and periodic training sequence, we obtain a closed-form expression for the synchronization parameters, hence greatly simplifying the algorithm complexity. Simulations demonstrate that the joint estimation method provides better accuracy than existing joint and separate sampling clock and carrier frequency offsets estimation algorithms.