Two-layer MiLAC beamforming with lossless reciprocal components achieves the same sum-rate as fully digital beamforming in multi-user MISO networks via a closed-form mapping and joint optimization of power and scattering matrices.
An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel
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Distributed two-timescale design for joint short-term precoder optimization and long-term 6DMA rotation updates in multi-cell systems using inter-cell interference power constraint coordination to maximize average weighted sum-rate.
A fully distributed OTA beamforming design for full-duplex cell-free massive MIMO that jointly optimizes UL/DL sum MSE while suppressing UE-to-UE pilot contamination via projection and best-response updates.
A multi-agent DRL framework for distributed precoding in cell-free massive MIMO within O-RAN achieves higher aggregate throughput than distributed baselines and similar performance to centralized methods with lower signaling overhead.
citing papers explorer
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Two-Layer Microwave Linear Analog Computer (MiLAC)-aided Multi-user MISO Networks
Two-layer MiLAC beamforming with lossless reciprocal components achieves the same sum-rate as fully digital beamforming in multi-user MISO networks via a closed-form mapping and joint optimization of power and scattering matrices.
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Multi-Cell 6DMA: Cooperative Interference Management and Antenna Rotation Optimization
Distributed two-timescale design for joint short-term precoder optimization and long-term 6DMA rotation updates in multi-cell systems using inter-cell interference power constraint coordination to maximize average weighted sum-rate.
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Over-the-Air Beamforming Design for Full-Duplex Cell-Free Massive MIMO Systems
A fully distributed OTA beamforming design for full-duplex cell-free massive MIMO that jointly optimizes UL/DL sum MSE while suppressing UE-to-UE pilot contamination via projection and best-response updates.
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Distributed Precoding for Cell-free Massive MIMO in O-RAN: A Multi-agent Deep Reinforcement Learning Framework
A multi-agent DRL framework for distributed precoding in cell-free massive MIMO within O-RAN achieves higher aggregate throughput than distributed baselines and similar performance to centralized methods with lower signaling overhead.