Research
Research Directions
WISELab develops mathematical models and learning algorithms for wireless communication, radio mapping, localization, and low-altitude network intelligence.
Theory and Methods
Tensor Signal Processing
Structured tensor models for sparse wireless measurements, spectrum maps, source localization, and MIMO beam-aware communications.
Theory and MethodsSequential Bayesian Learning
Learning hidden states from streams of uncertain observations through probabilistic filtering, smoothing, and decision making.
Applications
Low-altitude Signal Processing
Signal processing for UAV placement, aerial search, channel learning, and reliable low-altitude radio mapping.
ApplicationsPredictive Communications
Using mission trajectories and radio maps to plan routing, spectrum, timing, and power before links degrade.
ApplicationsSelf-localizing Radio Mapping
Constructing radio maps when measurements arrive without reliable location labels.
ApplicationsRadio Environment Sensing
Reconstructing radio maps and the hidden propagation environment from wireless measurements.