Geostatistics-inspired sparsity-aware cooperative spectrum sensing for cognitive radio networks

Abstract

A cognitive radio (CR) sensing problem is considered, where a number of CRs collaboratively detect the activity of an incumbent primary system. The proposed sensing framework is based on the novel concept of channel gain map, a geostatistics-inspired tool that allows to capture the spatiotemporal evolution of the propagation environment. The channel gain maps are updated by opportunistically reuse the primary channel idle periods. Also, the RF-power map, generated by the active sources, is tracked for spectrum spatial re-use and CR transmit power calibration purposes.