CSI feedback algorithm based on deep unfolding for massive MIMO systems
In order to solve the problem that the channel state information (CSI) feedback algorithm based on deep learning in massive MIMO systems at present had too many parameters to be trained and could not be explained well, two CSI feedback algorithms based on depth expansion were proposed.The first one...
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| Format: | Article |
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Editorial Department of Journal on Communications
2022-12-01
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| Series: | Tongxin xuebao |
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| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022237/ |
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| _version_ | 1841539973591859200 |
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| author | Yong LIAO Gang CHENG Yujie LI |
| author_facet | Yong LIAO Gang CHENG Yujie LI |
| author_sort | Yong LIAO |
| collection | DOAJ |
| description | In order to solve the problem that the channel state information (CSI) feedback algorithm based on deep learning in massive MIMO systems at present had too many parameters to be trained and could not be explained well, two CSI feedback algorithms based on depth expansion were proposed.The first one was approximate message delivery (AMP) algorithm based on learnable parameters.The learnable parameters in deep learning were used to replace the threshold value of the threshold function in the AMP algorithm and the parameters of the Onsage correction term.The nonlinear ability of threshold function in dealing with non-strict sparse data was enhanced.The other was the AMP algorithm based on convolutional network, which replaced the threshold function module with the convolutional residual learning module, and used the module to remove the Gaussian random noise generated by each iteration of the AMP algorithm.Simulation results show that the proposed two algorithms have better CSI feedback performance than AMP algorithm, and the AMP algorithm based on convolutional network has better CSI reconstruction performance than the representative method based on deep learning. |
| format | Article |
| id | doaj-art-608204f4aca543e79080d9085bb70bb7 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2022-12-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-608204f4aca543e79080d9085bb70bb72025-01-14T06:28:36ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2022-12-0143778859390971CSI feedback algorithm based on deep unfolding for massive MIMO systemsYong LIAOGang CHENGYujie LIIn order to solve the problem that the channel state information (CSI) feedback algorithm based on deep learning in massive MIMO systems at present had too many parameters to be trained and could not be explained well, two CSI feedback algorithms based on depth expansion were proposed.The first one was approximate message delivery (AMP) algorithm based on learnable parameters.The learnable parameters in deep learning were used to replace the threshold value of the threshold function in the AMP algorithm and the parameters of the Onsage correction term.The nonlinear ability of threshold function in dealing with non-strict sparse data was enhanced.The other was the AMP algorithm based on convolutional network, which replaced the threshold function module with the convolutional residual learning module, and used the module to remove the Gaussian random noise generated by each iteration of the AMP algorithm.Simulation results show that the proposed two algorithms have better CSI feedback performance than AMP algorithm, and the AMP algorithm based on convolutional network has better CSI reconstruction performance than the representative method based on deep learning.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022237/CSI feedbackdeep learningdeep unfoldingapproximate message passinglearnable parameter, convolutional network |
| spellingShingle | Yong LIAO Gang CHENG Yujie LI CSI feedback algorithm based on deep unfolding for massive MIMO systems Tongxin xuebao CSI feedback deep learning deep unfolding approximate message passing learnable parameter, convolutional network |
| title | CSI feedback algorithm based on deep unfolding for massive MIMO systems |
| title_full | CSI feedback algorithm based on deep unfolding for massive MIMO systems |
| title_fullStr | CSI feedback algorithm based on deep unfolding for massive MIMO systems |
| title_full_unstemmed | CSI feedback algorithm based on deep unfolding for massive MIMO systems |
| title_short | CSI feedback algorithm based on deep unfolding for massive MIMO systems |
| title_sort | csi feedback algorithm based on deep unfolding for massive mimo systems |
| topic | CSI feedback deep learning deep unfolding approximate message passing learnable parameter, convolutional network |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022237/ |
| work_keys_str_mv | AT yongliao csifeedbackalgorithmbasedondeepunfoldingformassivemimosystems AT gangcheng csifeedbackalgorithmbasedondeepunfoldingformassivemimosystems AT yujieli csifeedbackalgorithmbasedondeepunfoldingformassivemimosystems |