Integrated Sensing And Communication (ISAC)forms a symbiosis between the human need for communication and the need for increasing productivity, by extracting environmental information leveraging the communication network. As multiple sensory already create a perception of the environment, an investigation into the advantages of ISAC compare to such modalities is required. Therefore, we introduce MaxRay, an ISAC framework allowing to simulate communication, sensing, and additional sensory jointly. Emphasizing the challenges for creating such sensing networks, we introduce the required propagation properties for sensing and how they are leveraged. To compare the performance of the different sensing techniques, we analyze four commonly used metrics used in different fields and evaluate their advantages and disadvantages for sensing. We depict that a metric based on prominence is suitable to cover most algorithms. Further we highlight the requirement of clutter removal algorithms, using two standard clutter removal techniques to detect a target in a typical industrial scenario. In general a versatile framework, allowing to create automatically labeled datasets to investigate a large variety of tasks is demonstrated.
翻译:综合遥感和通信(ISAC)是人类通信需要与生产力提高需要之间的一种共生关系,通过利用通信网络提取环境信息来提高生产率。由于多种感官已经创造了对环境的看法,因此需要调查ISAC的优势与这种模式相比较。因此,我们引入了MaxRay,一个允许模拟通信、遥感和额外感官的ISAC框架。我们强调建立这种遥感网络的挑战,我们引入了所需的传播属性,用于遥感和如何利用这些网络。为了比较不同遥感技术的性能,我们分析了在不同领域使用的四种常用的计量,并评估了这些计量的利弊。我们描述了一种基于突出度的衡量标准适合涵盖大多数算法。我们进一步强调了使用两种标准的清除方法来探测典型工业情景中的目标的要求。一般地展示了一种多用途框架,允许创建自动标签的数据集来调查大量任务。