Channel estimation for OFDM system based on deep learning
An efficient channel estimation model based on deep learning was proposed for the problems of inter-carrier interference and inter-symbol interference in 5G system signal reception.The estimated channels were obtained through a preliminary estimation at the pilots.And they were treated as low resolu...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2023-12-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023240/ |
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| _version_ | 1841540020724301824 |
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| author | Yun ZHANG Jing ZHOU Jingwei HUANG Shujuan YU Liya HUANG |
| author_facet | Yun ZHANG Jing ZHOU Jingwei HUANG Shujuan YU Liya HUANG |
| author_sort | Yun ZHANG |
| collection | DOAJ |
| description | An efficient channel estimation model based on deep learning was proposed for the problems of inter-carrier interference and inter-symbol interference in 5G system signal reception.The estimated channels were obtained through a preliminary estimation at the pilots.And they were treated as low resolution images containing noise, which were input into the channel estimation model.By learning the mapping relationship between the low resolution images and the high resolution images, the noise in input channels was removed, and the high-resolution channel images were restored to obtain the entire channel state information eventually.The simulation results show that the model not only continues the advantages of traditional attention mechanisms in suppressing redundant information, reduces computational overhead, but also achieves good accuracy and robustness, and has good estimation performance for various channels. |
| format | Article |
| id | doaj-art-1ee39c351eaa4d248a6f9f5b2101bb23 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2023-12-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-1ee39c351eaa4d248a6f9f5b2101bb232025-01-14T06:22:29ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2023-12-014412413359384724Channel estimation for OFDM system based on deep learningYun ZHANGJing ZHOUJingwei HUANGShujuan YULiya HUANGAn efficient channel estimation model based on deep learning was proposed for the problems of inter-carrier interference and inter-symbol interference in 5G system signal reception.The estimated channels were obtained through a preliminary estimation at the pilots.And they were treated as low resolution images containing noise, which were input into the channel estimation model.By learning the mapping relationship between the low resolution images and the high resolution images, the noise in input channels was removed, and the high-resolution channel images were restored to obtain the entire channel state information eventually.The simulation results show that the model not only continues the advantages of traditional attention mechanisms in suppressing redundant information, reduces computational overhead, but also achieves good accuracy and robustness, and has good estimation performance for various channels.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023240/deep learningchannel estimationimage restorationattention mechanism |
| spellingShingle | Yun ZHANG Jing ZHOU Jingwei HUANG Shujuan YU Liya HUANG Channel estimation for OFDM system based on deep learning Tongxin xuebao deep learning channel estimation image restoration attention mechanism |
| title | Channel estimation for OFDM system based on deep learning |
| title_full | Channel estimation for OFDM system based on deep learning |
| title_fullStr | Channel estimation for OFDM system based on deep learning |
| title_full_unstemmed | Channel estimation for OFDM system based on deep learning |
| title_short | Channel estimation for OFDM system based on deep learning |
| title_sort | channel estimation for ofdm system based on deep learning |
| topic | deep learning channel estimation image restoration attention mechanism |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023240/ |
| work_keys_str_mv | AT yunzhang channelestimationforofdmsystembasedondeeplearning AT jingzhou channelestimationforofdmsystembasedondeeplearning AT jingweihuang channelestimationforofdmsystembasedondeeplearning AT shujuanyu channelestimationforofdmsystembasedondeeplearning AT liyahuang channelestimationforofdmsystembasedondeeplearning |