Hybrid DE-EM Algorithm for Gaussian Mixture Model-Based Wireless Channel Multipath Clustering
In this paper, the Gaussian mixture model (GMM) is introduced to the channel multipath clustering. In the GMM field, the expectation-maximization (EM) algorithm is usually utilized to estimate the model parameters. However, the EM widely converges into local optimization. To address this issue, a hy...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2019/4639612 |
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| _version_ | 1850163951573139456 |
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| author | Yupeng Li Jianhua Zhang Ruisi He Lei Tian Hewen Wei |
| author_facet | Yupeng Li Jianhua Zhang Ruisi He Lei Tian Hewen Wei |
| author_sort | Yupeng Li |
| collection | DOAJ |
| description | In this paper, the Gaussian mixture model (GMM) is introduced to the channel multipath clustering. In the GMM field, the expectation-maximization (EM) algorithm is usually utilized to estimate the model parameters. However, the EM widely converges into local optimization. To address this issue, a hybrid differential evolution (DE) and EM (DE-EM) algorithms are proposed in this paper. To be specific, the DE is employed to initialize the GMM parameters. Then, the parameters are estimated with the EM algorithm. Thanks to the global searching ability of DE, the proposed hybrid DE-EM algorithm is more likely to obtain the global optimization. Simulations demonstrate that our proposed DE-EM clustering algorithm can significantly improve the clustering performance. |
| format | Article |
| id | doaj-art-efa4e25871714e4ebef8e71fd8f9ab6d |
| institution | OA Journals |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-efa4e25871714e4ebef8e71fd8f9ab6d2025-08-20T02:22:05ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772019-01-01201910.1155/2019/46396124639612Hybrid DE-EM Algorithm for Gaussian Mixture Model-Based Wireless Channel Multipath ClusteringYupeng Li0Jianhua Zhang1Ruisi He2Lei Tian3Hewen Wei4Key Lab of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, ChinaState Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, ChinaState Key Lab of Rail Traffic and Safety, Beijing Jiaotong University, Beijing, ChinaState Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, ChinaNational Key Laboratory of Science and Technology on Blind Signal Processing, Chengdu, Sichuan, ChinaIn this paper, the Gaussian mixture model (GMM) is introduced to the channel multipath clustering. In the GMM field, the expectation-maximization (EM) algorithm is usually utilized to estimate the model parameters. However, the EM widely converges into local optimization. To address this issue, a hybrid differential evolution (DE) and EM (DE-EM) algorithms are proposed in this paper. To be specific, the DE is employed to initialize the GMM parameters. Then, the parameters are estimated with the EM algorithm. Thanks to the global searching ability of DE, the proposed hybrid DE-EM algorithm is more likely to obtain the global optimization. Simulations demonstrate that our proposed DE-EM clustering algorithm can significantly improve the clustering performance.http://dx.doi.org/10.1155/2019/4639612 |
| spellingShingle | Yupeng Li Jianhua Zhang Ruisi He Lei Tian Hewen Wei Hybrid DE-EM Algorithm for Gaussian Mixture Model-Based Wireless Channel Multipath Clustering International Journal of Antennas and Propagation |
| title | Hybrid DE-EM Algorithm for Gaussian Mixture Model-Based Wireless Channel Multipath Clustering |
| title_full | Hybrid DE-EM Algorithm for Gaussian Mixture Model-Based Wireless Channel Multipath Clustering |
| title_fullStr | Hybrid DE-EM Algorithm for Gaussian Mixture Model-Based Wireless Channel Multipath Clustering |
| title_full_unstemmed | Hybrid DE-EM Algorithm for Gaussian Mixture Model-Based Wireless Channel Multipath Clustering |
| title_short | Hybrid DE-EM Algorithm for Gaussian Mixture Model-Based Wireless Channel Multipath Clustering |
| title_sort | hybrid de em algorithm for gaussian mixture model based wireless channel multipath clustering |
| url | http://dx.doi.org/10.1155/2019/4639612 |
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