QuickSense: Fast and Energy-Efficient Channel Sensing for Dynamic Spectrum Acess Wireless Networks

Spectrum sensing, the task of discovering spectrum usage at a given location, is a fundamental problem in dynamic spectrum access networks. While sensing in narrow spectrum bands is well studied in previous work, wideband spectrum sensing is challenging since a wideband radio is generally too expensive and power consuming for mobile devices. Sequential scan, on the other hand, can be very slow if the wide spectrum band contains many narrow channels. In this paper, we propose an analog-filter based compressed spectrum sensing method, which is much faster than sequential scan and much cheaper than using a wideband radio. The key insight is that, if the sum of energy on a contiguous band is low, we can conclude that all channels in this band are available with just one measurement. Based on this insight, we design an intelligent search algorithm to minimize the number of measurements. We prove the algorithm is asymptotically optimal. We prototype our method using simple analog filters and analog energy detectors. Our evaluation using real TV "white space" signals shows the effectiveness of our algorithm.