CSI-CLIP++ uses CSI-CIR contrastive alignment to pretrain a channel encoder that improves beam prediction by up to 19.31 percentage points and supports positioning on DeepMIMO data across environments.
HeterCSI: Channel-adaptive heterogeneous CSI pretraining framework for gener- alized wireless foundation models
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
years
2026 5verdicts
UNVERDICTED 5representative citing papers
AirFM-DDA reparameterizes wireless channel data into the delay-Doppler-angle domain and uses efficient window attention to achieve better zero-shot performance on channel prediction and estimation with lower compute cost.
Physics-intrinsic wireless foundation model enforces wave equivariance to capture electromagnetic propagation and improve robustness to unseen environments.
Adaptive 3D-RoPE adapts rotary positional encoding to wireless channel physics via learnable 3D frequencies and dynamic CSI control, yielding up to 10.7 dB NMSE gains in scale extrapolation and 1 dB in zero-shot tasks.
A unified framework for CSI-native foundation models incorporates scale-aware exposure, physical coordinates, and correlation-bounded attention, reporting over 4 dB NMSE gains in zero-shot tasks and 36.6% spectral efficiency improvement with 7% pilot overhead.
citing papers explorer
-
CSI-CLIP++: A Scalable Channel Foundation Model for Wireless Communication via CIR-CSI Consistency
CSI-CLIP++ uses CSI-CIR contrastive alignment to pretrain a channel encoder that improves beam prediction by up to 19.31 percentage points and supports positioning on DeepMIMO data across environments.
-
AirFM-DDA: Air-Interface Foundation Model in the Delay-Doppler-Angle Domain for AI-Native 6G
AirFM-DDA reparameterizes wireless channel data into the delay-Doppler-angle domain and uses efficient window attention to achieve better zero-shot performance on channel prediction and estimation with lower compute cost.
-
Physics Equivariance for Robust Generalization in Wireless Foundation Model
Physics-intrinsic wireless foundation model enforces wave equivariance to capture electromagnetic propagation and improve robustness to unseen environments.
-
Adaptive 3D-RoPE: Physics-Aligned Rotary Positional Encoding for Wireless Foundation Models
Adaptive 3D-RoPE adapts rotary positional encoding to wireless channel physics via learnable 3D frequencies and dynamic CSI control, yielding up to 10.7 dB NMSE gains in scale extrapolation and 1 dB in zero-shot tasks.
-
Towards CSI-Native Foundation Models: A Channel-Adaptive Roadmap for 6G
A unified framework for CSI-native foundation models incorporates scale-aware exposure, physical coordinates, and correlation-bounded attention, reporting over 4 dB NMSE gains in zero-shot tasks and 36.6% spectral efficiency improvement with 7% pilot overhead.