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Sensors 2016, 16(7), 966; doi:10.3390/s16070966

A New Sparse Adaptive Channel Estimation Method Based on Compressive Sensing for FBMC/OQAM Transmission Network

College of Information Science & Technology, Hainan University, Haikou 570228, China
Faculty of International Tourism and Management, City University of Macau, Macau 999078, China
Department of Information Science & Technology, Qingdao University of Science & Technology, Qingdao 266061, China
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 17 April 2016 / Revised: 19 June 2016 / Accepted: 21 June 2016 / Published: 24 June 2016
(This article belongs to the Section Sensor Networks)
View Full-Text   |   Download PDF [2678 KB, uploaded 24 June 2016]   |  


The conventional channel estimation methods based on a preamble for filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) systems in mobile-to-mobile sensor networks are inefficient. By utilizing the intrinsicsparsity of wireless channels, channel estimation is researched as a compressive sensing (CS) problem to improve the estimation performance. In this paper, an AdaptiveRegularized Compressive Sampling Matching Pursuit (ARCoSaMP) algorithm is proposed. Unlike anterior greedy algorithms, the new algorithm can achieve the accuracy of reconstruction by choosing the support set adaptively, and exploiting the regularization process, which realizes the second selecting of atoms in the support set although the sparsity of the channel is unknown. Simulation results show that CS-based methods obtain significant channel estimation performance improvement compared to that of conventional preamble-based methods. The proposed ARCoSaMP algorithm outperforms the conventional sparse adaptive matching pursuit (SAMP) algorithm. ARCoSaMP provides even more interesting results than the mostadvanced greedy compressive sampling matching pursuit (CoSaMP) algorithm without a prior sparse knowledge of the channel. View Full-Text
Keywords: FBMC/OQAM; channel estimation; compressive sensing; sparse adaptive; greedy algorithm FBMC/OQAM; channel estimation; compressive sensing; sparse adaptive; greedy algorithm

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wang, H.; Du, W.; Xu, L. A New Sparse Adaptive Channel Estimation Method Based on Compressive Sensing for FBMC/OQAM Transmission Network. Sensors 2016, 16, 966.

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