An Optimal Sensing Framework Based on Spatial RSS-profile in Cognitive Radio Networks

In cognitive radio networks (CRNs), regulatory bodies, such as the FCC, enforce an extremely demanding detectability requirement to protect primary users' communications, which can hardly be achieved with one-time sensing using only a single sensor. Most of the previous work focused on either cooperative sensing or sensing scheduling as a viable means to improve the detection performance without studying their interactions. In this paper, we propose an optimal spectrum sensing framework in CRNs that jointly exploits sensors' cooperation and sensing scheduling to meet the desired detection performance with minimum sensing overhead. Specifically, we propose an optimal sensing framework for the IEEE 802.22 wireless regional area networks (WRANs) that directs the base station (BS) to manage spectrum sensing by (i) constructing each primary signal's spatial profile of received signal strengths (RSSs) as a detection criterion, (ii) selecting an optimal set of sensors for cooperative sensing, and (iii) finding an optimal time to stop sensing. This framework will ensure the desired sensing performance of 802.22 with minimum sensing overhead. Our evaluation results show that the proposed sensing algorithms reduce the sensing overhead significantly and lower the feasible operation region of energy detector by 13 dB for practical scenarios.