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Physics-Informed Unsupervised Learning for Reliable Beamforming in Cluttered MIMO-ISAC
In this paper, we consider joint beamforming and power allocation for a mobile multiuser MIMO integrated sensing and communication (ISAC) network with clutter, residual self-interference, and outdated channel state information, under per-user rate and sensing signal-to-interference-plus-noise ratio
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