Frame-based temporal occupancy characterization for compliance enforcement in opportunistic spectrum access networks

Abstract

Multi-channel access and spectrum agility represent significant challenges to temporal occupancy modelling for compliance enforcement of individual users/networks in opportunistic spectrum access (OSA) scenarios. In previous work, temporal occupancy estimation within spectrum bands was examined, when there was no requirement to track individual user/network behaviors. This approach was in line with the predominantly licensed-based access models where individual users/networks did not need to be tracked. However, depending upon the specific measurement objectives, discrimination between different users/networks may be required. In envisioned OSA scenarios, such tracking may be more difficult, given the dynamics of proposed OSA techniques, as well as the different network management infrastructures. In this work, the random temporal sampling approach for estimation of temporal spectrum occupancy parameters is expanded. A frame-based sampling inversion technique for spectrum occupancy estimation is proposed, which can be used for estimating temporal parameters for a given user/network of interest. In this approach, parameters from randomly sampled frames are used to characterize temporal occupancy. The performance of the proposed approach is examined for temporal occupancy characterization, including circumstances where the monitoring node misses frames due to the sampling design, sensor limitations or through error conditions on a given channel. The work further motivates the use of probabilistic characterization of spectrum occupancy for compliance enforcement, given the non-deterministic behavior of dynamic spectrum access mechanisms in emerging wireless network deployment scenarios.