UAV-Based 3D Spectrum Sensing in Spectrum-Heterogeneous Networks

In cognitive radio networks, collaborative spectrum sensing has been recognized as a key technology to enable secondary users (SUs) to detect spectrum holes and opportunistically access primary licensed spectrum band without harmful interference. Most of the existing studies focus on 1D or 2D spectrum opportunity detection and explicitly or implicitly assume that all SUs share the same spectrum opportunity. In this paper, we first investigate the issue of joint spatial-temporal spectrum sensing in 3D spectrum-heterogeneous space by leveraging the location flexibility of flying unmanned aerial vehicle (UAV) spectrum sensors. We divide the sensing space into three layers: black layer, grey layer, and white layer, which represent different spatial spectrum access opportunities. Then, we formulate the 3D spatial-temporal opportunity sensing model and derive the spatial-temporal false alarm and detection probabilities at both single UAV level and whole network level. Afterwards, we design a temporal fusion window and a spatial fusion sphere to address the composite spatial-temporal data fusion, called 3D spatial-temporal sensing (3DSTS). A comparison among 3DSTS, the benchmark 3D noncooperative sensing (3DNCS) and 3D cooperative sensing (3DCS) shows the inefficiency of the traditional sensing schemes in the 3D spectrum-heterogeneous networks. Furthermore, we develop three improved versions of 3DSTS, which show much better detection performance. To maximize the utilization of spectrum resource and minimize the interference to the PU, a sensing-based power control scheme is also proposed. Finally, numerical simulations corresponding to the theoretical analysis are demonstrated.