PC-SC: A Predictive Channel-Based Semantic Communication System for Sensing Scenarios
Due to its significant efficiency, semantic communication emerges as a promising technique for sixth-generation (6G) networks. The wireless propagation channel plays a crucial role in system design, as it directly impacts transmission performance and capability. Given the increasingly complex commun...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/14/3129 |
| _version_ | 1797589551349235712 |
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| author | Yutong Sun Jianhua Zhang Jialin Wang Li Yu Yuxiang Zhang Guangyi Liu Guofu Xie Ji Li |
| author_facet | Yutong Sun Jianhua Zhang Jialin Wang Li Yu Yuxiang Zhang Guangyi Liu Guofu Xie Ji Li |
| author_sort | Yutong Sun |
| collection | DOAJ |
| description | Due to its significant efficiency, semantic communication emerges as a promising technique for sixth-generation (6G) networks. The wireless propagation channel plays a crucial role in system design, as it directly impacts transmission performance and capability. Given the increasingly complex communication scenarios, the channel exhibits high dynamism and poses challenges in acquisition. In such cases, sensing-based methods have drawn significant attention. To enhance system robustness, we propose a predictive channel-based semantic communication (PC-SC) system tailored for sensing scenarios. The PC-SC system is designed with an orientation toward applications by directly taking semantic targets into account. It comprises three modules: transmitter, predictive channel, and receiver. Firstly, at the transmitter, instead of employing global semantic coding, the scheme emphasizes preserving semantic information through target-based semantic extraction. Secondly, the channel prediction module predicts the dynamic wireless channel by utilizing the extracted target-based semantic information. Finally, at the receiver, the target-based semantic information can be utilized to meet specific application requirements. Alternatively, pre-captured background and semantic targets can be composited to fulfill complete image reconstruction needs. We evaluate the proposed approach by using a sensing image transmission scenario as a case study. Experimental results demonstrate the superiority of the PC-SC system in terms of image reconstruction performance and cost savings of bit. We employ beam prediction as a channel prediction task and find that the targets-based method outperforms the complete image-based approach in terms of efficiency and robustness, which can provide 32% time-saving. |
| first_indexed | 2024-03-11T01:08:11Z |
| format | Article |
| id | doaj.art-c1faddafb1304c06bae4a447a2b887b8 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T01:08:11Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-c1faddafb1304c06bae4a447a2b887b82023-11-18T19:06:16ZengMDPI AGElectronics2079-92922023-07-011214312910.3390/electronics12143129PC-SC: A Predictive Channel-Based Semantic Communication System for Sensing ScenariosYutong Sun0Jianhua Zhang1Jialin Wang2Li Yu3Yuxiang Zhang4Guangyi Liu5Guofu Xie6Ji Li7State Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaState Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaFuture Research Laboratory, China Mobile Research Institute, Beijing 100053, ChinaHunan Xiangjiang Intelligent Science and Technology Innovation Center Co., Ltd., Changsha 410000, ChinaThe State Radio Monitoring_Center Testing Center, Beijing 100037, ChinaDue to its significant efficiency, semantic communication emerges as a promising technique for sixth-generation (6G) networks. The wireless propagation channel plays a crucial role in system design, as it directly impacts transmission performance and capability. Given the increasingly complex communication scenarios, the channel exhibits high dynamism and poses challenges in acquisition. In such cases, sensing-based methods have drawn significant attention. To enhance system robustness, we propose a predictive channel-based semantic communication (PC-SC) system tailored for sensing scenarios. The PC-SC system is designed with an orientation toward applications by directly taking semantic targets into account. It comprises three modules: transmitter, predictive channel, and receiver. Firstly, at the transmitter, instead of employing global semantic coding, the scheme emphasizes preserving semantic information through target-based semantic extraction. Secondly, the channel prediction module predicts the dynamic wireless channel by utilizing the extracted target-based semantic information. Finally, at the receiver, the target-based semantic information can be utilized to meet specific application requirements. Alternatively, pre-captured background and semantic targets can be composited to fulfill complete image reconstruction needs. We evaluate the proposed approach by using a sensing image transmission scenario as a case study. Experimental results demonstrate the superiority of the PC-SC system in terms of image reconstruction performance and cost savings of bit. We employ beam prediction as a channel prediction task and find that the targets-based method outperforms the complete image-based approach in terms of efficiency and robustness, which can provide 32% time-saving.https://www.mdpi.com/2079-9292/12/14/31296G communicationsemantic targetssemantic communicationchannel predictionsensing scenariosimage transmission |
| spellingShingle | Yutong Sun Jianhua Zhang Jialin Wang Li Yu Yuxiang Zhang Guangyi Liu Guofu Xie Ji Li PC-SC: A Predictive Channel-Based Semantic Communication System for Sensing Scenarios Electronics 6G communication semantic targets semantic communication channel prediction sensing scenarios image transmission |
| title | PC-SC: A Predictive Channel-Based Semantic Communication System for Sensing Scenarios |
| title_full | PC-SC: A Predictive Channel-Based Semantic Communication System for Sensing Scenarios |
| title_fullStr | PC-SC: A Predictive Channel-Based Semantic Communication System for Sensing Scenarios |
| title_full_unstemmed | PC-SC: A Predictive Channel-Based Semantic Communication System for Sensing Scenarios |
| title_short | PC-SC: A Predictive Channel-Based Semantic Communication System for Sensing Scenarios |
| title_sort | pc sc a predictive channel based semantic communication system for sensing scenarios |
| topic | 6G communication semantic targets semantic communication channel prediction sensing scenarios image transmission |
| url | https://www.mdpi.com/2079-9292/12/14/3129 |
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