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Found 6 papers, 0 papers with code
Vision-Assisted Digital Twin Creation for mmWave Beam Management
In the context of communication networks, digital twin technology provides a means to replicate the radio frequency (RF) propagation environment as well as the system behaviour, allowing for a way to optimize the performance of a deployed system based on simulations.
Transformer-Based Neural Surrogate for Link-Level Path Loss Prediction from Variable-Sized Maps
The transformer model attends to the regions that are relevant for path loss prediction and, therefore, scales efficiently to maps of different size.
Beyond Codebook-Based Analog Beamforming at mmWave: Compressed Sensing and Machine Learning Methods
Analog beamforming is the predominant approach for millimeter wave (mmWave) communication given its favorable characteristics for limited-resource devices.
MIMO-GAN: Generative MIMO Channel Modeling
We propose generative channel modeling to learn statistical channel models from channel input-output measurements.
Neural RF SLAM for unsupervised positioning and mapping with channel state information
The model is based on an encoder-decoder architecture.
Neural Augmentation of Kalman Filter with Hypernetwork for Channel Tracking
Through extensive experiments on CDL-B channel model, we show that the HKF can be used for tracking the channel over a wide range of Doppler values, matching Kalman filter performance with genie Doppler information.
