论文标题
汽车互联网的语义交流:一种多用户合作方法
Semantic Communication for Internet of Vehicles: A Multi-User Cooperative Approach
论文作者
论文摘要
预计车辆互联网(IOV)将成为中央基础设施,向连接的车辆和用户提供高级服务,以提高运输效率和安全性。各种新兴应用程序/服务带来了对连接车辆和路边单元(RSU)之间移动数据流量的爆炸性增长,这对IOV造成了频谱稀缺的重大挑战。在本文中,我们提出了一个合作的语义意识架构,以传达从协作用户到降低数据流量的服务器的基本语义。与当前的解决方案相反,这些解决方案主要基于在句法通信方面堆积高度复杂的信号处理技术和多个访问功能,本文提出了IOV中语义吸引内容的想法。具体而言,追求源数据基本语义的成功传输,而不是准确接收符号,无论其含义与常规句法通信的含义如何。为了评估拟议的体系结构的好处,我们为智能运输系统中车辆的图像检索任务提供了一个案例研究。仿真结果表明,所提出的体系结构以较少的无线电资源(尤其是在低信噪比(SNR)制度中,都可以比现有的解决方案的表现,这可以阐明在极端环境中扩展应用程序时所提出的架构的潜力。
Internet of Vehicles (IoV) is expected to become the central infrastructure to provide advanced services to connected vehicles and users for higher transportation efficiency and security. A variety of emerging applications/services bring explosively growing demands for mobile data traffic between connected vehicles and roadside units (RSU), imposing the significant challenge of spectrum scarcity to IoV. In this paper, we propose a cooperative semantic-aware architecture to convey essential semantics from collaborated users to servers for lowering the data traffic. In contrast to current solutions that are mainly based on piling up highly complex signal processing techniques and multiple access capabilities in terms of syntactic communications, this paper puts forth the idea of semantic-aware content delivery in IoV. Specifically, the successful transmission of essential semantics of the source data is pursued, rather than the accurate reception of symbols regardless of its meaning as in conventional syntactic communications. To assess the benefits of the proposed architecture, we provide a case study of the image retrieval task for vehicles in intelligent transportation systems. Simulation results demonstrate that the proposed architecture outperforms the existing solutions with fewer radio resources, especially in a low signal-to-noise-ratio (SNR) regime, which can shed light on the potential of the proposed architecture in extending the applications in extreme environments.