Research

Current Research Interests

• Digital Twin of EM Propagation Environments

• Radio Propagation, Measurements, and Channel Modeling

• mmWave and THz Communications

• High-Speed Railway Communications, LTE-Railways, GSM-Railways, 5G-Railways

• 5G Massive MIMO and High Frequency Communication Techniques

• Big Data, Artificial Intelligence, and Cloud Computing in Wireless Communications

Scholarly Contributions:

Wireless Channel Characterization and Modeling for High-Speed Rail (HSR) Systems 

Over the past decade, I have pioneered the development of foundational frameworks for wireless channel characterization and modeling in High-Speed Rail (HSR) systems across sub-6 GHz, millimeter-wave (mmWave), and terahertz (THz) bands (~300 GHz), addressing the critical challenge of ensuring ultra-reliable communications under extreme mobility. As the principal architect of this research paradigm, I conceived original ideas, established the core methodologies, and led their translation into practical tools and international standards, bringing the following three key innovations from concept to global adoption:

1. Measurement-Ray-Tracing Fusion Paradigm: I conceived and implemented a novel paradigm that synergizes sparse real-world measurements with advanced deterministic ray-tracing. This innovation shattered the "speed-frequency bottleneck," solving the critical limitation of acquiring high-frequency channel data at operational speeds of 500 km/h. It enables robust, high-fidelity channel simulation for mmWave/THz bands in high-mobility scenarios where traditional exhaustive measurement methods fail, providing a viable path for system design without prohibitive field campaigns.

2. Comprehensive HSR Channel Model Library: Building on the fusion paradigm, I established the comprehensive channel model library for HSR scenarios spanning from sub-6 GHz to mmWave. These models implement low-complexity yet high-fidelity methodologies, directly eliminating the long-standing, two-decade global challenge of lacking scenario-specific channel models for accurate and large-scale railway network planning and optimization.

3. Pioneering THz Framework for Smart Rail Mobility: I pioneered the inaugural theoretical and modeling framework for THz (~300 GHz) channels in high-speed rail. This framework strategically balances computational efficiency with propagation accuracy to meet real-time system constraints. Its core principles became the cornerstone of IEEE’s first THz communication standard (802.15.3d-2017), setting the benchmark for next-generation rail communication research.

With my models forming China’s Railway Industry Standard and influencing 3GPP guidelines, my work directly supports mission-critical deployments across over 40,000 km of China's HSR network. This contribution is uniquely recognized by my double IEEE VTS Neal Shepherd Best Propagation Paper Awards (2019, 2022), making me the only researcher to be first-author honored twice, and underscores my work as the backbone of next-generation rail communications.

Digital Twin of 3D Spatial Sensing Integrated Wireless Autonomous Networks

Over the past decade, I have led the development of TwinSWAN, addressing critical challenges in 3D spatial sensing, realistic electromagnetic environment data generation, and autonomous network optimization. As the principal scientist of TwinSWAN, I developed original ideas, designed the entire system architecture, conducted independent research on key technologies, and led diverse talented researchers and engineers to bring the following three platforms from concept to reality:

(1) 3D Wireless Observer: Upgrades the monitoring of electromagnetic environments from 2D ground to 3D space. With a sophisticated design based on my expertise in electromagnetic wave propagation sounding, the multiple Unmanned Aerial Vehicles (UAVs) are equipped with devices that transmit and receive signals to capture the wireless environment's characteristics and create a comprehensive 3D radio propagation map agilely, increasing the efficiency of channel impulse response measurements by 30,000 times and reducing storage requirements by 100 times.

(2) High-Performance Ray Tracer: Under my innovation on sparse representation of scattering points and hybrid modeling on wave propagation mechanisms, this first and only open-access high-performance ray tracing platform can generate precise 3D spatial electromagnetic wave propagation data in real-time, which digital twins the wireless channel and strongly supports network optimization, benefiting over 10,000 users from more than 100 countries and endorsed by leading institutions from industry and academia.

(3) AI Network Optimizer: Integrated with advanced AI algorithms tailored for optimizing wireless networks developed by me, this versatile mobile communication link-level/system-level platform can feed back the optimization commands to real wireless networks without human supervision, truly realizing the autonomous optimization and evolution of real wireless networks.

With more than 10,000 users from more than 100 countries, including numerous institutions in the telecommunication industry and innovation, such as Intel, Thales, VIAVI, Samsung, Sony, China Mobile, Huawei, and ZTE, TwinSWAN leads to smarter, more efficient, and reliable networks, such as 5G and beyond, vehicle-x communications, and space-air-ground integrated networks (SAGIN). In 2024, TwinSWAN won the IET Excellence and Innovation Awards in the International Award (Submissions outside UK and Europe).