AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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BeamRMX is proposed, which is the first dedicated framework to treat the spatial radiation pattern as the primary BeamRM query and learn how scene geometry transforms it into the received power field, and shows consistent gains over deterministic and diffusion baselines.
Experiments show that the proposed approach achieves spectral efficiency close to exact SVD-based beamforming in single-stream transmission and consistently improves multi-stream sum-rate over representative learned baselines, indicating good scalability for low-latency wireless processing.
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