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This paper presents a systematic machine learning study of 6G-IoT beamforming optimization, comparing network, environmental, device, and vision feature groups for predictive power, and applying clustering methods to enhance performance.
This paper proposes a self-evolving in-context learning framework for direct pilot-to-beamformer design in multi-user MISO systems, integrating a Transformer backbone with a pilot encoder-decoder network and curriculum learning to handle multiple channel models without retraining.
A Rotman lens is a passive electronic component used for beamforming in radio frequency applications, enabling multiple antenna beams without phase shifters. It was invented by Walter Rotman and R.F. Turner in 1963.
A detailed account of building a mmWave radar prototype that uses FMCW, Capon beamforming, and a neural network to classify building materials, with a focus on detecting asbestos in walls.
This paper presents Agentic-LTPO, a nested bilevel optimization framework that uses agentic AI to adapt physical layer configurations under dynamic operator policies, achieving 57.2% long-term performance improvement in cell-free MIMO beamforming.