These crowdsensing systems are limited by the uplink bandwidth available to backhaul the raw in-phase and quadrature (IQ) samples and power spectrum density (PSD) data needed to run various applications. The wireless community has recently risen to this challenge in designing spectrum monitoring systems that utilize many low-cost spectrum sensors to gather large volumes of sampled data across space, time, and frequencies. Understanding spectrum activity is challenging when attempted at scale. These promising results suggest that Snoopy is an intriguing option in bringing the ability of spectrum sensing to the masses, thereby truly enabling crowdsourcing options in this domain.
Although such a construction might not match the precision of the most sophisticated but expensive spectrum analyzers, we show that by leveraging some carefully designed spectral features, Snoopy can achieve decent accuracy in determining TV whitespaces (512 - 698 MHz) - it can detect primary signals at up to - 90dBm with an error rate of 15%, while achieving a median error of < 4dB in estimating the power of these signals. Through the use of suitable frequency translators, such a view can be flexibly shifted to other spectrum bands. It achieves this by leveraging the spectral scan functionality available in certain 802.11 NICs (e.g., the Atheros 9280 family of chipsets), which provides an unique lens towards the WiFi spectrum (2.4 GHz). To address this challenge, Snoopy augments popular mobile devices with a small attachable hardware unit (RF frequency translator) that can provide a reasonable view of the wireless spectrum across different frequency bands.
Since typical spectrum analyzers are specialized hardware that is both expensive to acquire and cumbersome to carry around, they are rarely available for quick-and-easy spectrum sensing while on the go.
We propose Snoopy, a system that can translate one's mobile phone or tablet into a low-cost, yet effective RF spectrum analyzer.
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