A two-part biLSTM model estimates environmental scattering from sequential pilots and adaptively tunes RIS configurations to achieve lower localization RMSE than random, codebook, or non-adaptive baselines in dynamic rich scattering environments.
PhysFad: Physics-Based End-to-End Channel Modeling of RIS-Parametrized Environments With Adjustable Fading
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A biLSTM controller adaptively senses RIS-assisted rich scattering environments and designs beamforming vectors to achieve low UE localization error in simulations.
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Adaptive RIS Configuration Design with Environmental Sensing for User Localization in Dynamic Rich Scattering Environment
A two-part biLSTM model estimates environmental scattering from sequential pilots and adaptively tunes RIS configurations to achieve lower localization RMSE than random, codebook, or non-adaptive baselines in dynamic rich scattering environments.
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Integrated Sensing, User Location and Orientation Estimation in RIS-Assisted Dynamic Rich Scattering Environment
A biLSTM controller adaptively senses RIS-assisted rich scattering environments and designs beamforming vectors to achieve low UE localization error in simulations.