Algorithm and Performance Analysis for Frame Detection Based on Matched Filtering

Frame arrival detection is the first crucial task for a digital communication receiver. In this paper, we propose a new frame arrival detection method based on the concept of matched filtering. The proposed training sequence consists of three repeated subsequences, each including a few repeated segments and exhibiting high sparsity in frequency domain. The proposed detection method includes the following two stages. The first matched filtering stage employs the subsequence as the filter coefficients, which matches the frequency sparsity of the received subsequence and could greatly improve the output signal to noise ratio. The second stage adopts delayed autocorrelation on the filtered signal to detect the presence of training sequence. It is demonstrated that the proposed method could outperform the conventional methods in terms of both missed detection and false alarm probability. We derive the theoretical analysis for both missed detection and false alarm performance. We further extend our performance analysis and numerical evaluation to the system with carrier frequency offset (CFO). The results illustrate accuracy of the analytical results and robustness of the proposed method against practical levels of CFO.