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Chong Han

Researcher at Shanghai Jiao Tong University

Publications -  133
Citations -  4589

Chong Han is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Computer science & Communication channel. The author has an hindex of 19, co-authored 98 publications receiving 2642 citations. Previous affiliations of Chong Han include University of Electronic Science and Technology of China & Georgia Institute of Technology.

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Channel Measurement and Path-Loss Characterization for Low-Terahertz Indoor Scenarios

TL;DR: In this paper, a wideband channel measurement campaign at 140 GHz and 220 GHz is conducted in indoor scenarios including a meeting room and an office room, where directional antennas are utilized and rotated for resolving the multi-path components (MPCs) in the angular domain.
Journal ArticleDOI

On Beamforming Gain Models for Performance Evaluation and Analysis of Narrowband and Wideband Wireless Networks

TL;DR: The effectiveness and importance of the proposed general beamforming gain model are revealed, particularly for millimeter-wave wideband systems.
Journal ArticleDOI

Dynamic-Subarray With Fixed Phase Shifters for Energy-Efficient Terahertz Hybrid Beamforming Under Partial CSI

TL;DR: An energy-efficient dynamic-subarray with fixed-phase-shifters (DS-FPS) architecture is proposed for THz hybrid beamforming and extensive simulation results show that, the proposed DS-F PS architecture with the RSD and RBR algorithms achieves much higher energy efflciency than the existing architectures.

300 GHz Wideband Channel Measurement and Analysis in a Lobby

TL;DR: In this paper , a wideband channel measurement campaign in a 500-square-meter indoor lobby at 306-321 GHz is presented, where the measurement system consists of a vector network analyzer (VNA)-based channel sounder, and a directional antenna equipped at the receiver to resolve multi-path components (MPCs) in the angular domain.

Transformer-based GAN for Terahertz Spatial-Temporal Channel Modeling and Generating

TL;DR: In this paper , a transformer-based generative adversarial network modeling method (T-GAN) is proposed in the Terabit-per-second (Tbps) band, which exploits the advantage of GAN in modeling the complex distribution, and the powerful expressive capability of transformer structure.