Spatio-Temporal Fusion for Small-scale Primary Detection in Cognitive Radio Networks

Abstract—In cognitive radio networks (CRNs), detecting smallscale primary devices—such as wireless microphones (WMs)— is a challenging, but very important, problem that has not yet been addressed well. We identify the data-fusion range as a key factor that enables effective cooperative sensing for detection of small-scale primary devices. In particular, we derive a closed-form expression for the optimal data-fusion range that minimizes the average detection delay. We also observe that the sensing performance is sensitive to the accuracy in estimating the primary’s location and transmit-power. Based on these observations, we propose an efficient sensing framework, called DeLOC, that iteratively performs location/transmit-power estimation and dynamic sensor selection for cooperative sensing. Our extensive simulation results in a realistic CRN environment show that DeLOC achieves near-optimal detection performance, while meeting the detection requirements specified in the IEEE 8...

• Type: Journal
• Year: 2010
• Where: INFOCOM
• Authors: Alexander W. Min, Xinyu Zhang, Kang G. Shin
• Keywords: Communications, Data-fusion Range, Detection, INFOCOM 2010, Sensing