In-band spectrum sensing in cognitive radio networks: energy detection or feature detection?
Proceedings of the 14th ACM international conference on Mobile computing and networking
Assessment of urban-scale wireless networks with a small number of measurements
Proceedings of the 14th ACM international conference on Mobile computing and networking
SenseLess: A Database-Driven White Spaces Network
IEEE Transactions on Mobile Computing
Exploring indoor white spaces in metropolises
Proceedings of the 19th annual international conference on Mobile computing & networking
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Unlicensed, secondary users of TV whitespaces today rely on spectrum occupancy databases to determine what spectrum they can use for their communication needs. In this paper, we first show that such spectrum databases (that depend solely on propagation models as per guidelines of the FCC in the USA) can be quite inaccurate leading to under-utilization of spectrum. Next, we propose that these spectrum databases can be significantly augmented using opportunistic measurements when possible. Instead of incorporating primary detection functions in each secondary device, we propose to use vehicle-mounted spectrum sensors that collect and report measurements from the road, which can serve as useful "anchor points" to enhance existing propagation models. We have currently deployed a version of our system on a single public transit bus traveling across Madison, WI, in the USA. Based on measurements collected at over 1 million locations across a 100 square-km area, we find commercial databases tend to over-predict the coverage of certain TV broadcasts, unnecessarily blocking the usage of whitespace spectrum over large area (up to 42% measured locations). We further propose a model-fitting approach that refines existing propagation models with measurements, reclaiming a substantial amount of wasted area (up to 33% measured locations).