7 citations · 18 across the 16 of their papers we have counts for
12 papers · 1 filter
A Hybrid Model-Assisted Approach for Path Loss Prediction in Suburban Scenarios
Chenlong Wang, Bo Ai, Ruiming Chen +5
Accurate path loss prediction is crucial for wireless network planning and optimization in suburban environments with complex terrain variation and diverse land cover. This paper p…
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 Geometry Map-Based Site-Specific Propagation Channel Model for Urban Scenarios
Junzhe Song, Ruisi He, Mi Yang +4
With the rapid deployments of 5G and 6G networks, accurate modeling of urban radio propagation has become critical for system design and network planning. However, conventional sta…
A Novel Site-Specific Inference Model for Urban Canyon Channels: From Measurements to Modeling
Junzhe Song, Ruisi He, Mi Yang +4
With the rapid development of intelligent transportation and smart city applications, urban canyon has become a critical scenario for the design and evaluation of wireless communic…
Deep Learning Based Dynamic Environment Reconstruction for Vehicular ISAC Scenarios
Junzhe Song, Ruisi He, Mi Yang +5
Integrated Sensing and Communication (ISAC) technology plays a critical role in future intelligent transportation systems, by enabling vehicles to perceive and reconstruct the surr…
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…