Date of Award
Bachelor of Science
With the increasing use of wireless technologies, we see a heavy use of the spectrum at certain frequencies whereas it is underutilized at other frequencies. We need to utilize the currently underutilized spectrum. Hence, a paradigm called Dynamic Spectrum Access arises. Dynamic Spectrum Access looks for opportunity to utilize this underutilized spectrum by allowing devices to opportunistically access spectrum that is not actively used. DSA, however, requires spectrum sensing and spectrum characterization across time, space, and frequency for opportunistic devices to know where to operate. Spectrum sensing is the process of collecting power level traces from the radio-frequency spectrum, whereas spectrum characterization determines how many transmitters occupy a given spectrum and what are their temporal and frequency characteristics. Traditional spectrum sensing and characterization is performed with expensive sensors, which renders the task economically-infeasible. Our project introduces a low-cost alternative, which is more mobile and cost efficient. A typical issue with low cost sensors is that the scans from the low-cost sensor are of lower quality compared to scans from a higher-cost alternative. In this end, we compare the characterizations of the spectrum from the low cost sensor to the high-cost sensor across time, frequency, and space. We conduct granularity, sensitivity,transmitter pattern, and mobility experiments to compare the scans of the two sensors in different scenarios. We analyze the two characterizations from the two sensors in a controlled setting to see if the scans of the two are comparable. From the mobility and granularity experiments, we observe that scans from the low-cost sensors are comparable to the scans from the high-cost sensors. However, as expected, we do see lower sensitivity in the low-cost sensor. Comparing the two scans will help us form a better picture of the kind of ii infrastructure we can build using the two sensors that is both economically feasible and can give us high-fidelity scans.
Misra, Stuti, "High-Fidelity Spectrum Characterization with Low-Cost Sensors" (2017). Computer Science. 5.