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- W4224925138 abstract "We consider multi-input multi-output (MIMO) dual function radar communication (DFRC) systems, and design a transmit beamforming matrix that optimizes a weighted combination of the radar estimate Cramer-Rao bound (CRB) and the communication rate. A hybrid beamforming structure is considered, with fewer RF chains than antennas, to achieve the benefits of MIMO systems while maintaining low cost. However, such a structure may have a rank-deficient beamforming matrix, resulting in degraded estimation performance. We propose antenna selection as means to ensure a full-rank beamforming matrix, and also select the communication channels so that high communication rate can be achieved. A learning approach is employed to optimally select antennas and design the corresponding beamforming matrix. By leveraging a combination of softmax neural networks, the proposed solution is able to optimize the joint performance metric for a DFRC system." @default.
- W4224925138 created "2022-04-28" @default.
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- W4224925138 date "2022-05-23" @default.
- W4224925138 modified "2023-09-23" @default.
- W4224925138 title "Cramér-Rao Bound and Antenna Selection Optimization for Dual Radar-Communication Design" @default.
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- W4224925138 doi "https://doi.org/10.1109/icassp43922.2022.9747651" @default.
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