Integrated Sensing and Communication for 6G: Ten Key Machine Learning Roles
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by
Umut Demirhan, Ahmed Alkhateeb
2022
Abstract
Integrating sensing and communication is a defining theme for future wireless
systems. This is motivated by the promising performance gains, especially as
they assist each other, and by the better utilization of the wireless and
hardware resources. Realizing these gains in practice, however, is subject to
several challenges where leveraging machine learning can provide a potential
solution. This article focuses on ten key machine learning roles for joint
sensing and communication, sensing-aided communication, and communication-aided
sensing systems, explains why and how machine learning can be utilized, and
highlights important directions for future research. The article also presents
real-world results for some of these machine learning roles based on the
large-scale real-world dataset DeepSense 6G, which could be adopted in
investigating a wide range of integrated sensing and communication problems.
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