{"title":"Semantic Communication Empowered Collaborative Perception in Constrained Networks","authors":"Yuntao Liu;Qian Huang;Rongpeng Li;Zhifeng Zhao;Shuyuan Zhao;Yuan Liu;Yongdong Zhu;Honggang Zhang","doi":"10.1109/LWC.2024.3520660","DOIUrl":null,"url":null,"abstract":"Traditional collaborative perception methods typically focus on optimizing perception performance in ideal wireless transmission conditions. However, in real-world constrained networks, it is crucial for collaborative perception schemes to alleviate network load while ensuring performance robustness. To address this challenge, this letter introduces S2CP, a Semantic Communication empowered Collaborative Perception framework. Within the S2CP, we propose the Multi-scale Dilated Cross-Attention (MDCA) module to effectively extract task-oriented valuable semantic features for transmission, thereby minimizing data transmission overhead and improving perception performance. Furthermore, to mitigate feature distortion during wireless transmission, we develop a pre-training strategy utilizing Masked AutoEncoders (MAE) to enhance the robustness of S2CP. Experimental results demonstrate that S2CP significantly enhances perception performance while substantially reducing network transmission volume.","PeriodicalId":13343,"journal":{"name":"IEEE Wireless Communications Letters","volume":"14 3","pages":"701-705"},"PeriodicalIF":4.6000,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Wireless Communications Letters","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10810363/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Traditional collaborative perception methods typically focus on optimizing perception performance in ideal wireless transmission conditions. However, in real-world constrained networks, it is crucial for collaborative perception schemes to alleviate network load while ensuring performance robustness. To address this challenge, this letter introduces S2CP, a Semantic Communication empowered Collaborative Perception framework. Within the S2CP, we propose the Multi-scale Dilated Cross-Attention (MDCA) module to effectively extract task-oriented valuable semantic features for transmission, thereby minimizing data transmission overhead and improving perception performance. Furthermore, to mitigate feature distortion during wireless transmission, we develop a pre-training strategy utilizing Masked AutoEncoders (MAE) to enhance the robustness of S2CP. Experimental results demonstrate that S2CP significantly enhances perception performance while substantially reducing network transmission volume.
期刊介绍:
IEEE Wireless Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of wireless communications. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of wireless communication systems.