MaxRay: A Raytracing-based Integrated Sensing and Communication Framework
This work addresses the need for better simulation tools to evaluate ISAC against other sensing modalities, though it appears incremental as it builds on existing raytracing and clutter removal methods.
The authors introduced MaxRay, a raytracing-based framework for simulating integrated sensing and communication (ISAC) to compare sensing techniques and generate labeled datasets, demonstrating its versatility for tasks like clutter removal in industrial scenarios.
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.