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Sparse compression algorithm for MBOK signals

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Abstract

To cope with the limitations of traditional direct-sequence spread spectrum system application, MBOK signals have been considered owing to their high gain, fast rate, and high frequency band transmission capability. However, to address the problems of large search range, slow speed, and large complexity when receiving and searching for MBOK signals, the sparse compression search (SCS) algorithm is proposed. The idea of the SCS algorithm is to compress the frequency dimension in order to improve the frequency compensation efficiency, and to then establish the sparse processing from the code dimension and the frequency dimension, thus improving the search speed. Next, the code and frequency values are calculated by channel mapping matching. The test and analysis results show that the SCS algorithm can quickly estimate the code and frequency values, and the detection probability and the computation speed are much better than other algorithms.

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Acknowledgments

This work was financially supported by the National Natural Science Foundation of China (Grant No. 61501309), the China Postdoctoral Science Foundation (Grant Nos. 2017T100185), and the Liaoning Natural Science Foundation of China (Grant No. 2017011002-301). The author declares that all the data in this paper are real and availability.

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Authors and Affiliations

  1. School of Information Science and Engineering, Shenyang Ligong University, Shenyang, 110159, China

    Fang Liu

  2. Graduate School, Shenyang Ligong University, Shenyang, 110159, China

    Yongxin Feng

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  1. Fang Liu
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  2. Yongxin Feng
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Correspondence to Fang Liu.

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Liu, F., Feng, Y. Sparse compression algorithm for MBOK signals. SIViP 13, 861–869 (2019). https://doi.org/10.1007/s11760-019-01422-7

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  • DOI: https://doi.org/10.1007/s11760-019-01422-7

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