Analysis and Design of Correlation-Enhanced Preamble for OFDM Coarse Synchronization

‍ ‍Orthogonal frequency-division multiplexing （OFDM） technology is widely used in the communications field. Since OFDM requires orthogonal subcarriers， the synchronization accuracy greatly affects the transmission quality. Therefore， synchronization for OFDM has been a key research point in communications. First， synchronization with preambles can be divided into two categories： autocorrelation and cross-correlation. This paper analyzes the characteristics of autocorrelation and cross-correlation synchronization methods. In particular， the distributions and limitations of the four classic autocorrelation methods from S&C， Minn， Park， and Ren， and another Two-Stage approach are discussed. The complexity of the theoretical formula and the iterative calculation complexity of the above algorithms are also compared. On this basis， correlation-enhanced timing and frequency synchronization for OFDM are proposed， including the preamble， matched timing metric， and method of carrier frequency offset estimation. The main idea is to introduce correlation among preambles， increase the amount of data samples when calculating， and avoid side peaks in the timing metric. The accuracy of our synchronization method is improved by increasing the computational complexity. In addition， the timing synchronization method supports iterative calculation and facilitates hardware implementation. When comparing the performance of different methods， the accuracy of timing synchronization is estimated by the probability that the maximum value of the timing metric falls within the guard interval of the received signal. The accuracy of frequency offset estimation is expressed by the mean square error （MSE） of the normalized frequency offset. The simulation results show that the accuracy of timing synchronization is better than other classic autocorrelation methods and is close to that of the two-stage approach under the additive white Gaussian noise （AWGN） channel and the two-path channel， but the complexity of the proposed method is less than that of the Two-Stage approach. Furthermore， owing to the higher accuracy of timing synchronization， the performance of the proposed frequency offset estimation under the AWGN channel is better than other classic autocorrelation methods. With 20 dB as the boundary under a two-path channel， the performance of the proposed frequency offset estimation is better when the signal-to-noise ratio is below 20 dB.