Abstract
Although blind source separation of convolutive mixtures can be efficiently solved in the frequency domain, the problem of permutation ambiguity must be solved. Thus, this paper proposes an improved permutation algorithm. Firstly, the improved algorithm uses energy correlation of the separated signal to sort the signals of each frequency bin. Then, the reliability of the sorting of the signals on the frequency bin will be judged according to the threshold. The unreliable frequency bins will be corrected in time so that we can obtain the separated signal accurately, eventually. This algorithm effectively reduces sorting errors and error propagation, thereby improving the separation effect. BSS experiments are performed on the voice signals and radar signals under different convolutive mixing models. The simulation results show that the improved algorithm has better separation performance and higher robustness than the traditional permutation algorithms, which is reflected by the increasing signal to interference ratio of separated signals.
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Acknowledgements
We gratefully acknowledge the anonymous reviewers who read the drafts and provided many helpful suggestions.
Funding
This work is supported by the National Natural Science Foundation of China (61876143) and the Natural Science Foundation of Shanghai (19ZR1454000).
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Yichen Zhao, Weihong Fu and Chunhua Zhou. The first draft of the manuscript was written by Yichen Zhao and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Zhao, Y., Fu, W., Zhou, C. et al. Energy Correlation Permutation Algorithm of Frequency-Domain Blind Source Separation Based on Frequency Bins Correction. Wireless Pers Commun 120, 1753–1768 (2021). https://doi.org/10.1007/s11277-021-08533-w
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DOI: https://doi.org/10.1007/s11277-021-08533-w