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Integrated Sensing and Communication for 6G: Ten Key Machine Learning Roles

Umut DemirhanAhmed Alkhateeb
Aug 2022
摘要
Integrating sensing and communication is a defining theme for future wirelesssystems. This is motivated by the promising performance gains, especially asthey assist each other, and by the better utilization of the wireless andhardware resources. Realizing these gains in practice, however, is subject toseveral challenges where leveraging machine learning can provide a potentialsolution. This article focuses on ten key machine learning roles for jointsensing and communication, sensing-aided communication, and communication-aidedsensing systems, explains why and how machine learning can be utilized, andhighlights important directions for future research. The article also presentsreal-world results for some of these machine learning roles based on thelarge-scale real-world dataset DeepSense 6G, which could be adopted ininvestigating a wide range of integrated sensing and communication problems.
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