LAUSR

Integrated sensing and communication (ISAC) is emerged as a research hotspot of key technologies in future wireless communication systems with the purpose of achieving environment sensing within a wireless communication framework. To achieve complete and accurate sensing of the large-scale complex environment, multiple views from different user equipments (UEs) and base stations (BSs) in a wireless network should be fully and cooperatively exploited. In this article, both centralized and distributed architectures of multi-view sensing for wireless communications are proposed. For each architecture, the key performance indicators are pointed out. To realize the multi-view sensing, various signal processing as well as machine learning methods are discussed with detailed classifications and comparisons. Simulation results verify the effectiveness of the proposed architectures and schemes.