4 papers · 1 filter
ODE-Former for Mobile Channel Prediction: A Novel Learning Structure Leveraging The Physics Continuity
Zhuoran Xiao
Obtaining accurate channel state information (CSI) is crucial and challenging for multiple-input multiple-output (MIMO) wireless communication systems. With the increasing antenna…
From Data-driven Learning to Physics-inspired Inferring: A Novel Mobile MIMO Channel Prediction Scheme Based on Neural ODE
Zhuoran Xiao, Zhaoyang Zhang, Zirui Chen +3
In this paper, we propose an innovative learning-based channel prediction scheme so as to achieve higher prediction accuracy and reduce the requirements of huge amounts and strict…
Mobile MIMO Channel Prediction with ODE-RNN: a Physics-Inspired Adaptive Approach
Zhuoran Xiao, Zhaoyang Zhang, Zirui Chen +2
Obtaining accurate channel state information (CSI) is crucial and challenging for multiple-input multiple-output (MIMO) wireless communication systems. Conventional channel estimat…
C-GRBFnet: A Physics-Inspired Generative Deep Neural Network for Channel Representation and Prediction
Zhuoran Xiao, Zhaoyang Zhang, Chongwen Huang +3
In this paper, we aim to efficiently and accurately predict the static channel impulse response (CIR) with only the user's position information and a set of channel instances obtai…