6 papers
Artificial Intelligence Empowered Channel Prediction: A New Paradigm for Propagation Channel Modeling
Ruisi He, Mi Yang, Zhengyu Zhang +2
This paper proposes a novel paradigm centered on Artificial Intelligence (AI)-empowered propagation channel prediction to address the limitations of traditional channel modeling. W…
A CGAN-LSTM-Based Framework for Time-Varying Non-Stationary Channel Modeling
Keying Guo, Ruisi He, Mi Yang +5
Time-varying non-stationary channels, with complex dynamic variations and temporal evolution characteristics, have significant challenges in channel modeling and communication syst…
Channel Semantic Characterization for Integrated Sensing and Communication Scenarios: From Measurements to Modeling
Zhengyu Zhang, Ruisi He, Bo Ai +4
With the advancement of sixth-generation (6G) wireless communication systems, integrated sensing and communication (ISAC) is crucial for perceiving and interacting with the environ…
Measurement-Based Non-Stationary Markov Tapped Delay Line Channel Model for 5G-Railways
Xuejian Zhang, Ruisi He, Mi Yang +7
5G for Railways (5G-R) is globally recognized as a promising next-generation railway communication system designed to meet increasing demands. Channel modeling serves as foundation…
Vision-Aided Channel Prediction Based on Image Segmentation at Street Intersection Scenarios
Xuejian Zhang, Ruisi He, Mi Yang +4
Intelligent vehicular communication with vehicle road collaboration capability is a key technology enabled by 6G, and the integration of various visual sensors on vehicles and infr…
Vision Aided Channel Prediction for Vehicular Communications: A Case Study of Received Power Prediction Using RGB Images
Xuejian Zhang, Ruisi He, Mi Yang +3
The communication scenarios and channel characteristics of 6G will be more complex and difficult to characterize. Conventional methods for channel prediction face challenges in ach…