Online assessment of sensing performance in experimental spectrum sensing platforms

Dynamic Spectrum Access aims at exploiting underutilized frequency bands towards improving wireless network performance. In this context, spectrum sensing is employed, in order to monitor spectrum occupancy and drive appropriate adaptation decisions. Researchers in the field primarily evaluate proposed sensing approaches in terms of detection accuracy and efficiency of free spectrum utilization. In this work, we focus on online assessment of spectrum occupancy with respect to sensing delay and energy efficiency. Evaluation of spectrum sensing methods with respect to these two metrics is rather lagging in recent experimental developments. The first is related to the latency induced by the spectrum sensing process and its impact on sensing efficiency, which is tightly connected to the resulting performance of the cognitive solution. On the other hand, energy consumption is considered as a crucial issue in all types of wireless communications. Therefore, it is important to extend existing testbed experimentation tools and develop new ones, in order to equip cognitive testbeds with such advanced monitoring capabilities. To this aim, we integrated the proposed monitoring procedure with the experimentation tools of the CREW testbed federation. In order to demonstrate the applicability of our framework, we experimentally validate the performance of four different sensing platforms, as well as a real-time spectrum sensing engine that implements parallel processing on software defined radios, in terms of the aforementioned metrics.