The growing role that artificial intelligence and specifically machine learning is playing in shaping the future of wireless communications has opened up many new and intriguing research directions. This paper motivates the research in the novel direction of \textit{vision-aided wireless communications}, which aims at leveraging visual sensory information in tackling wireless communication problems. Like any new research direction driven by machine learning, obtaining a development dataset poses the first and most important challenge to vision-aided wireless communications. This paper addresses this issue by introducing the Vision-Wireless (ViWi) dataset framework. It is developed to be a parametric, systematic, and scalable data generation framework. It utilizes advanced 3D-modeling and ray-tracing softwares to generate high-fidelity synthetic wireless and vision data samples for the same scenes. The result is a framework that does not only offer a way to generate training and testing datasets but helps provide a common ground on which the quality of different machine learning-powered solutions could be assessed.
翻译:人工智能和具体机器学习在塑造无线通信的未来方面正在发挥越来越大的作用,这已经开启了许多新的和令人感兴趣的研究方向。本文件激励了对新方向的研究,该方向旨在利用视觉感官信息解决无线通信问题。与机器学习所驱动的任何新的研究方向一样,获得发展数据集对愿景辅助无线通信构成第一个也是最重要的挑战。本文件通过引入愿景-无线(ViWi)数据集框架来解决这一问题。它是一个参数、系统化和可扩展的数据生成框架。它利用先进的3D建模和射线软件为同一场景生成高真知觉合成无线和视觉数据样本。其结果不仅为生成培训和测试数据集提供了途径,而且有助于提供一个共同基础,据以评估不同机器学习能力解决方案的质量。