37 citations · 41 across the 7 of their papers we have counts for
5 papers · 1 filter
Rethinking Radiomap Blind Prediction with Limited Environment and Configuration Representations
Xiaojie Li, Yu Han, Han Fang +3
Radiomap blind prediction infers radiomaps from observable representations of the propagation environment and base station (BS) configuration without field measurements. These repr…
Radar-Aided Near-Field Beam Prediction via Beam Map Learning for XL-MIMO V2I Communications
Jiali Nie, Yu Han, Yuanhao Cui +3
Near-field beam training in extremely large-scale multiple-input multiple-output (XL-MIMO) vehicle-to-infrastructure (V2I) systems incurs high overhead due to large range-angle cod…
Wideband Precoding for U6G XL-MIMO Systems: Beam Squint Boundaries and Channel Slicing
Zhizheng Lu, Yu Han, Xiaojie Li +2
The unconventionally large aperture of extremely large-scale multiple-input multiple-output (XL-MIMO) arrays, in conjunction with the wider bandwidths in the upper-6 GHz (U6G) freq…
U6G XL-MIMO Radiomap Prediction: Multi-Config Dataset and Beam Map Approach
Xiaojie Li, Yu Han, Zhizheng Lu +2
The upper 6 GHz (U6G) band with XL-MIMO is a key enabler for sixth-generation wireless systems, yet intelligent radiomap prediction for such systems remains challenging. Existing d…
RadioGAT: A Joint Model-based and Data-driven Framework for Multi-band Radiomap Reconstruction via Graph Attention Networks
Xiaojie Li, Songyang Zhang, Hang Li +7
Multi-band radiomap reconstruction (MB-RMR) is a key component in wireless communications for tasks such as spectrum management and network planning. However, traditional machine-l…