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Gao, X. (ECE) – Engineering Wireless Systems Where Infrastructure Fails: Low-Power Through-Wall Communication for Nuclear-Facility Monitoring, UAV-Assisted Localization for Post-Disaster Search and Re at Engineering 2, Dec 1

Gao, X. (ECE) – Engineering Wireless Systems Where Infrastructure Fails: Low-Power Through-Wall Communication for Nuclear-Facility Monitoring, UAV-Assisted Localization for Post-Disaster Search and Re

When: Tue, Dec 1, 2026 · 2:00 PM – 3:30 PM
Where: Engineering 2 · Engineering 2 1156 High Street, Santa Cruz, CA, 95064 · Directions ↗
Price: Price not listed
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This dissertation presents wireless systems for three operating environments without the usual infrastructure: the containment building of a nuclear facility, the area affected by a natural disaster, and a field of sensors with no network of their own. Each system is engineered to an operational requirement and tested against it by measurement or simulation. The through-wall communication system carries monitoring data through a nuclear containment wall, replacing cable wiring that radiation damages. A battery-powered sub-GHz ultra-wideband (UWB) multicarrier transmitter inside containment reaches a receive array outside; a water-filling algorithm is reformulated to minimize transmit power for a required throughput, and a single-ray through-wall channel model matches measurements on a one-meter wall to about 0.1dB. At the 0.2W of an earlier UWB system, the simulated link supports about 780Mbps, whereas that system delivered under 10Mbps. The search-and-rescue localization framework locates survivors of earthquakes, wildfires, or floods from their phones’ beacons, using unmanned aerial vehicles (UAVs) with antenna arrays, when transmit power, path loss, and line-of-sight (LOS) or non-line-of-sight (NLOS) state are unknown. A deep-learning classifier labels each link, and the labels select the estimator: weighted least squares, an iterative second-order cone program with a bounded bias, or a label-aware projection for LOS, NLOS, and mixed environments, respectively. With the classifier in the loop on simulated NYUSIM channels, the end-to-end error is 46.8m, against 66.3m for the strongest baseline; the labeled data are public. The UAV-assisted status-update system maintains fresh status information at a ground station (GS) from unconnected sensors with an energy-limited, half-duplex UAV. The objective is the age of information (AoI) at the GS, because a collected but undelivered update does not reduce it.

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