Measurement-Augmented Spectrum Databases for White Space Spectrum

Abstract

Spectrum databases used to estimate TV white space availability often provide inaccurate and largely conservative estimates as they are primarily based on empirical propagation models. This leads to 'loss' of white space spectrum that is critical in urban areas with large spectrum demand. While alternatives are possible in terms of incorporating direct spectrum measurements, the measurement locations must be judiciously chosen so that measurement effort is not prohibitive. Fundamentally, this boils down to addressing the estimation accuracy vs measurement effort question. We present a rigorous data driven analysis to address this using measurement data collected in parts of New York City metro area. We show that it is possible to develop models that estimate whether the current database estimates are reliable in a given location. Following this, we provide a recipe for developing a 'measurementaugmented' spectrum database that takes the help of measurements where needed and falls back on the current propagation modelbased database technique in the rest of the areas. The final takeaway is that it is possible to improve database accuracy significantly with only modest amount of measurements.

Efficient placement of edge computing devices for vehicular applications in smart cities

“…For instance, access to the TV white space is usually controlled through a white space database that provides information to end-devices about unused bands by location [35]. However, such databases can provide inaccurate information, thereby resulting in increased interference [36] and reduced offloading gain. The goal is to characterize the effect of such inaccuracies on communications.…”

“…The WSDB makes these decisions based on spatio-temporal data of historical spectrum usage by licensed users [45], signal propagation models [46,47] and reliable terrain data [46,48]. However, experimental evaluations of WSDBs show that the information they provide may be inaccurate [36,49], for instance, due to malicious users reporting incorrect locations [50].…”

Efficient TV white space database construction via spectrum sensing and spatial inference

“…According to the FCC report, F-curves, a particular propagation model, is used by several approved spectrum databases [13]. It defines the protection contours of the TV channel.…”

Multi-channel sensing and resource allocation in energy constrained cognitive radio networks

“…In practice, information of state transition probabilities is not readily available due to sparse spectrum activity over long term. Existing spectrum availability studies only document duty cycle of a channel which is the probability of a channel being occupied by a PU [24][25][26][27]. Also, the works mentioned above considered CR systems with a single PU channel with fixed target detection probability as PU's QoS criteria.…”