Multi-Band UE Coordination Under Mobility
I am developing MCMB-HDT (Multi-Cell Multi-Band Handset Digital Twin), a UE-centric framework that couples real urban geometry, base-station topology, FR1/FR3/mmWave ray tracing, embodied handset antenna radiation, pedestrian motion, handset pose, and measurement-limited feedback. On top of this twin, we study Transformer-based rate prediction from sparse asynchronous histories and PPO-based power-aware array/band activation under rate, power, and exploration constraints.
This figure shows how geographic data are converted into a 3D digital-twin scene for multi-band ray-tracing simulation.
The capacity maps illustrate why the best band and antenna choice changes with location, handset pose, and pedestrian mobility.
The UE layout defines the active antenna elements and frequency bands used by the prediction and activation policies.
The policy result summarizes the tradeoff between exploration risk and achievable rate when the handset activates only a subset of arrays and bands.
Related papers
- Transformer-Based Rate Prediction for Multi-Band Cellular Handsets (IEEE ICC Workshops 2026)
- MCMB-HDT: A Multi-Cell Multi-Band Handset Digital Twin for Learning-Based Closed-Loop Array Activation (IEEE JSAC, under review)
Haozhe Lei (Graduate Student Member, IEEE) is a Ph.D. candidate in Electrical and Computer Engineering at New York University, advised by Professor Sundeep Rangan in NYU WIRELESS. He received the B.E. degree in electrical engineering and automation from China Agricultural University in 2019 and the M.S. degree in computer engineering from NYU in 2022. His research develops uncertainty-aware wireless intelligence for embodied autonomy and adaptive 6G systems, combining algorithms, digital twins, and physical testbeds to transform sparse RF and multimodal observations into calibrated spatial beliefs and closed-loop decisions.
His current work includes MC-CLE and LOCUS-DT for posterior RF localization, PIRL and wireless digital-twin priors for zero-shot robot navigation, MCMB-HDT for closed-loop multi-band handset adaptation, and object-centric graph memory for multimodal spatial reasoning. He also builds FR3/mmWave RFSoC/Pi-Radio channel-sounding systems with TurtleBot4 and Jackal UGV platforms. He received the 2023 Ernst Weber Fellowship from the NYU Tandon School of Engineering.