移动通信2024，Vol.48Issue(7)：95-100,6.DOI:10.3969/j.issn.1006-1010.20240625-0002
基于语义通信的协同感知系统
Cooperative Perception Based on Semantic Communication
摘要
Abstract
Compared to single-vehicle perception,cooperative perception provides a wider sensing range,playing a crucial role in 3D object detection for autonomous driving.Utilizing V2V communication technology,connected autonomous vehicles can share their sensor information(LiDAR point clouds)to achieve cooperative perception.We propose an innovative cooperative perception semantic communication scheme that uses importance maps to extract key semantic information and includes intermediate fusion functionality.Additionally,this architecture can be adapted to handle challenging time-varying multipath fading channels.To mitigate distortions caused by such channels,an explicit orthogonal frequency division multiplexing module that combines channel estimation and channel equalization is employed.Simulation results show that the proposed model outperforms traditional source-channel separate coding across various channel models.Robustness studies indicate that only a portion of the semantic information is crucial for effective cooperative perception.Despite being trained on a specific channel,the model learns a robust encoding of semantic information that remains effective across different channel models,demonstrating its generality and robustness.关键词
协同感知/V2V通信/语义通信/机器学习/时变多径衰落Key words
cooperative sensing/V2Vcommunication/semantic communication/machine learning/time-varying multipath fading分类
信息技术与安全科学引用本文复制引用
孙雨馨,陆茗轶,刘彦迪,黄欣宜,盛玉成,韩瑜,梁乐..基于语义通信的协同感知系统[J].移动通信,2024,48(7):95-100,6.基金项目
中央高校基本科研业务费专项资金(2242023K5003) （2242023K5003）
