New publication: Aleksandr Zavodovski, Suzan Bayhan, Jussi Kangasharju, Data-Driven Analysis of Database-Assisted Spectrum Access for Mobile Users, in Proceedings of IEEE Infocom Workshop on Advances in Software Defined and Context-Aware Cognitive Networks, Atlanta, GA, USA, May 2017.

Title: Data-Driven Analysis of Database-Assisted Spectrum Access for Mobile Users 

Abstract: White space databases (WSDB) have relieved the mobile devices from the challenge of spectrum sensing at low signal levels by introducing sensing-as-a-service approach. On the other hand, the regulations for WSDB-based spectrum access have asserted very strict constraints for mobile secondary users (SU). According to the US regulations, a mobile SU must query the WSDB anew each time as it relocates 100 meters. This requirement is problematic for mobile users, since car moving at moderate speed will hardly have a chance to access the spectrum at all, because of average latency of a WSDB query. In this paper, we analyze the spatiotemporal changes in the TV white spaces (TVWS) to develop more insights on the current regulations and performance enhancements for mobile scenarios. More particularly, we simulate realistic usage of mobile devices and analyze spatiotemporal accessibility variations of TVWS using a large data set of observations. Using a publicly-available geolocation database, we monitor the TVWS spectrum for about 6 months for 9 routes in different locations across the US. We report on the change in number of free channels on a route, the variations in the availability of a particular channel over a time period, maximum permitted transmission powers, WSDB response time, and channel lease times. Studying spatiotemporal changes in TVWS, we find that current TVWS ecosystem is inherently static and displays minimal temporal variations. This observation supports the criticism that current regulations are very conservative especially for mobile usage and suggests that spectrum information caching would be efficient.