Title: Frame synchronisation based on compressed sensing with correlation rule

Authors: Chaojin Qing; Xiucheng Dong; Hong Peng; Mintao Zhang; Kai Deng

Addresses: School of Electrical and Information Engineering, Xihua University, Chengdu, 610039, China ' School of Electrical and Information Engineering, Xihua University, Chengdu, 610039, China ' School of Electrical and Information Engineering, Xihua University, Chengdu, 610039, China ' School of Electrical and Information Engineering, Xihua University, Chengdu, 610039, China ' School of Physics and Electronic Engineering, Yibin University, Yibin, 644000, China

Abstract: The research of frame synchronisation, which processing is based on the sampling at Nyquist rate in traditional method, has been become the hot topic over the past few decades. In the light of compressed sensing theory that sampling received signals below the Nyquist rate, a frame synchronisation method with correlation rule is proposed in this paper. Firstly, the synchronisation metrics of frame synchronisation is expressed as compressed mode by developing the sparsity of the synchronisation metric amplitudes over observation window. The measurement matrix for compressive sampling is then projected, and compressive sampling for the received signal is employed according to the projected measurement matrix. Finally, we reconstruct the synchronisation metrics from the compressive sampling by utilising compressive sampling matching pursuit (CoSaMP) algorithm and obtain the estimate of frame synchronisation with the reconstructed synchronisation metrics. Compared to the traditional methods, the analysis and simulation results show that the sampling rate in proposed method is significantly reduced while obtaining comparative correct synchronisation probability when received signal-to-noise ratio (SNR) is relatively high. Simultaneously, for the reason that the correct synchronisation probability is not particularly sensitive to the iteration number of the CoSaMP algorithm for frame synchronisation, low reconstruction complexity is also obtained in the proposed method.

Keywords: compressed sensing; frame synchronisation; correlation rules; synchronisation metrics; compressive sampling; simulation; signal-to-noise ratio; SNR.

DOI: 10.1504/IJICT.2016.079120

International Journal of Information and Communication Technology, 2016 Vol.9 No.3, pp.271 - 281

Available online: 13 Sep 2016 *

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