Bayesian frame synchronization using periodic preamble for OFDM-based WLANs

In this letter, the principles of Bayesian changepoint detection are applied to the problem of frame synchronization in wireless systems that use a periodic training signal as part of the packet preamble. An autocorrelation-based metric is used, which allows modeling the synchronization problem as a problem of changepoint detection of a Gaussian process. A MAP estimator for the changepoint is derived that suits the wireless scenario. Examples and comparisons are made using the IEEE 802.11a OFDM standard. It is demonstrated that the proposed method has advantages over some existing synchronization approaches in terms of accuracy, latency, and/or complexity.