5 papers
MAPLE-RF: Efficient Probabilistic RF Source Localization in Partially Explored Environments
Haozhe Lei, Sundeep Rangan
Localizing a radio-frequency (RF) transmitter from received signals often requires a model of the environment to predict how obstacles block and reflect the signal. In many robotic…
MAGNETAR: Multipath-Guided Spatial Posteriors for Transmitter Pose Inference in the Upper Mid-Band
Haozhe Lei, Ruibin Chen, Yuhan Jiang +3
Robots that localize a radio transmitter need more than a point estimate: in cluttered rooms, one measurement is often consistent with several transmitter locations and, because up…
LOCUS-DT: Localization via Observation-Conditioned Uncertainty Scoring with Digital Twins
Haozhe Lei, Roberto Bomfin, Marwa Chafii +1
Accurate indoor localization is essential for emerging applications in robotic navigation and search and rescue. While classical methods typically focus on single-point estimates,…
Beyond Point Estimates: Likelihood-Based Full-Posterior Wireless Localization
Haozhe Lei, Hao Guo, Tommy Svensson +1
Modern wireless systems require not only position estimates, but also quantified uncertainty to support planning, control, and radio resource management. We formulate localization…
Transformer-Based Rate Prediction for Multi-Band Cellular Handsets
Ruibin Chen, Haozhe Lei, Hao Guo +4
Cellular wireless systems are facing a proliferation of frequency bands over a wide spectrum, particularly with the expansion into FR3. These bands must be supported in user equipm…