Cloud-Assisted Geolocation-Driven Dynamic Spectrum Access in Cognitive Radio Networks

Existing wireless devices and wireless networks use Radio Frequency (RF) bands in an exclusive manner, and different wireless devices cannot communicate with each other due to their hardwired radio functions. Furthermore, on one hand, almost all usable RF bands are already allocated to different wireless applications/providers leaving no room for further development of future wireless technologies. On the other hand, most of the already allocated bands are underutilized (less than 15%) or idle most of the time. Thus, cognitive radio networks (CRNs) have recently been researched to make the under-utilized spectrum available to unlicensed secondary users in an opportunistic manner. However, past studies are generally based on simulations which cannot mimic the real wireless environments. In this work, we will develop a test bed for dynamic spectrum access in CRNs using Software Defined Radio (SDR) devices such as National Instrument’s Universal Software Radio Peripheral (USRP) devices and Microsoft SORA kits. These devices use geolocation of idle spectrum to create a database for unlicensed users to search through for idle channels and use them dynamically. Cloud computing is used to process the large amounts of data about geolocation of idle bands and to match the geolocation of unlicensed users with that of idle bands on behalf of secondary users so as not to create any harmful interference to licensed primary users. In this work, we present the configuration of a test bed and some experimental results for cloud-assisted geolocation-driven dynamic spectrum access in cognitive radio networks. This project is funded by US National Science Foundation (NSF) under Grant CNS-1405670