A DRL-based framework for clustered cell-free networking reduces channel estimation overhead to a single measurement per AP and adapts to user mobility, outperforming prior clustering methods in simulations across multiple objectives.
Network MIMO with linear zero- forcing beamforming: Large system analysis, impact of channel esti- mation, and reduced-complexity scheduling
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Leveraging Deep Reinforcement Learning for Clustered Cell-Free Networking Over User Mobility
A DRL-based framework for clustered cell-free networking reduces channel estimation overhead to a single measurement per AP and adapts to user mobility, outperforming prior clustering methods in simulations across multiple objectives.