Deep Cooperation in ISAC System: Resource, Node and Infrastructure Perspectives
Zhiqing Wei, Haotian Liu, Zhiyong Feng, Huici Wu, Fan Liu, Qixun Zhang, Yucong Du
Abstract
With the emerging Integrated Sensing and Communication (ISAC) technique, exploiting the mobile communication system with multi-domain resources, multiple network elements, and large-scale infrastructures to realize cooperative sensing is a crucial approach satisfying the requirements of high-accuracy and large-coverage sensing in Internet of Everything (IoE). In this article, the deep cooperation in ISAC system including three perspectives is investigated. In the microscopic perspective, namely, within a single node, the sensing information carried by time-frequency-space-code multi-domain resources is processed, such as phase compensation, coherent accumulation and other operations, thereby improving the sensing accuracy. In the mesoscopic perspective, the sensing accuracy could be improved through the cooperation of multiple nodes. We explore various multi-node cooperative sensing scenarios and present the corresponding challenges and future research trends. In the macroscopic perspective, the massive number of infrastructures from the same operator or different operators could perform cooperative sensing to extend the sensing coverage and improve the sensing continuity. We investigate network architecture, target tracking methods, and the digital twin assisted large-coverage cooperative sensing. Simulation results demonstrate the superiority of multi-node and multi-resource cooperative sensing over non-cooperative sensing. This article may provide a deep and comprehensive view on the cooperative sensing in ISAC system to enhance the performance of sensing, supporting the applications of IoE.