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Found 5 papers, 1 papers with code
Channel Modeling for FR3 Upper Mid-band via Generative Adversarial Networks
The upper mid-band (FR3) has been recently attracting interest for new generation of mobile networks, as it provides a promising balance between spectrum availability and coverage, which are inherent limitations of the sub 6GHz and millimeter wave bands, respectively.
Zero-Shot Wireless Indoor Navigation through Physics-Informed Reinforcement Learning
To equip the navigation agent with sample-efficient learning and {zero-shot} generalization, this work proposes a novel physics-informed RL (PIRL) where a distance-to-target-based cost (standard in e2e) is augmented with physics-informed reward shaping.
Multi-Frequency Channel Modeling for Millimeter Wave and THz Wireless Communication via Generative Adversarial Networks
Evaluation of these systems requires statistical models that can capture the joint distribution of the channel paths across multiple frequencies.
Wireless Channel Prediction in Partially Observed Environments
Site-specific radio frequency (RF) propagation prediction increasingly relies on models built from visual data such as cameras and LIDAR sensors.
Parametrization and Estimation of High-Rank Line-of-Sight MIMO Channels with Reflected Paths
In these scenarios, standard channel models based on plane waves cannot capture the curvature of each wave front necessary to model spatial multiplexing.
