MiLAC combiner matches fully digital CRB for DOA estimation of K targets with 2 RF chains per target when row space spans the 2K-dimensional steering-derivative subspace.
Physics-compliant modeling and optimization of MIMO sys- tems aided by microwave linear analog computers
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MiLAC-aided beamforming with quantization-aware EE optimization improves energy efficiency at moderate spectral efficiency cost and expands the SE-EE operating region versus digital and hybrid methods.
MiLAC-aided MIMO radar achieves identical CRB and DoA performance to fully-digital baselines while cutting hardware via analog-domain beamforming and 2D-DFT.
GIM-based MiLAC precoding outperforms PIM by optimizing the power-flexibility tradeoff via SVD and WMMSE algorithms in downlink multiuser MISO systems.
LJAPOF is a learning-based framework that jointly designs MiLAC architectures and analog beamforming for lossy MIMO systems, outperforming stem- and fully-connected baselines in SE and EE by balancing interference suppression against hardware losses.
citing papers explorer
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How Many RF Chains Does a Microwave Linear Analog Computer (MiLAC) Need to Match the Fully-Digital Cram\'er-Rao Bound?
MiLAC combiner matches fully digital CRB for DOA estimation of K targets with 2 RF chains per target when row space spans the 2K-dimensional steering-derivative subspace.
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Quantization-Aware EE Optimization and SE-EE Tradeoff for MiLAC-Aided MU-MISO Beamforming
MiLAC-aided beamforming with quantization-aware EE optimization improves energy efficiency at moderate spectral efficiency cost and expands the SE-EE operating region versus digital and hybrid methods.
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Microwave Linear Analog Computer (MiLAC)-Aided MIMO Radar Sensing: Transmit Beamforming Design and DoA Estimation
MiLAC-aided MIMO radar achieves identical CRB and DoA performance to fully-digital baselines while cutting hardware via analog-domain beamforming and 2D-DFT.
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Microwave Linear Analog Computers Aided Multiuser Communication: General Impedance Matching and Precoding Optimization
GIM-based MiLAC precoding outperforms PIM by optimizing the power-flexibility tradeoff via SVD and WMMSE algorithms in downlink multiuser MISO systems.
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Lossy Microwave Linear Analog Computer (MiLAC) for Future MIMO: Learning-based Architecture Designs for Spectral and Energy Efficiency Maximization
LJAPOF is a learning-based framework that jointly designs MiLAC architectures and analog beamforming for lossy MIMO systems, outperforming stem- and fully-connected baselines in SE and EE by balancing interference suppression against hardware losses.