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Wireless signals and networks are ubiquitous in today’s world. Though more reliable than ever, wireless networks still struggle with weak coverage, blind spots, and interference. Having a strong understanding of wireless signal propagation is essential for increasing coverage, optimizing performance, and minimizing interference for wireless networks. Extensive studies have been done on the propagation of wireless signals, and many theoretical models have been made to simulate wireless signal propagation. Unfortunately, models of signal propagation are often not accurate in reality, and real- world signal measurements are required for validation.
Existing methods for collecting wireless measurements involve human researchers walking to each location of interest and manually collecting measurements, which requires large amounts of time and effort, or placing sensors at each location of interest, which is costly. We propose Drone- Sense: a system for measuring wireless signals using autonomous drones. DroneSense reduces the time and effort required for measurement collection, and is affordable and accessible to all users. This is significant in the field of wireless networking as it provides researchers with an efficient method to quickly analyze wireless coverage and test their wireless propagation models.
Senior Honors Thesis. Advisor: Xia Zhou.
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Ethan Yu, "Automating 3D Wireless Measurements with Drones." Dartmouth Computer Science Technical Report TR2016-796, May 2016.
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