Date of Award
Master of Science
Electrical and Computer Engineering
The successful implementation and employment of various cognitive radio services are largely dependent on the spectrum sensing performance of the cognitive radio terminals. Previous works on detection of cognitive radio have suggested the necessity of user cooperation in order to be able to detect at low signal-to-noise ratios experienced in practical situations. This report provides a brief overview of the impact of different fusion strategies on the spectrum hole detection performance of a fusion center in a distributed detection environment. Different decision or detection rule and fusion strategies, like single sensor scenario, counting rule, and linear decision metric, were used to analyze their influence on the spectrum sensing performance of the cognitive radio network. We consider a system of cognitive radio users who cooperate with each other in trying to detect licensed transmissions. Assuming that the cooperating nodes use identical energy detectors, we model the received signals as correlated log-normal random variables and study the problem of fusing the decisions made by the individual nodes. The cooperating radios were assumed to be designed in such a way that they satisfy the interference probability constraint individually. The interference probability constraint was also met at the fusion center. The simulation results strongly suggests that even when the observations at the individual sensors are moderately correlated, it is important not to ignore the correlation between the nodes for fusing the local decisions made by the secondary users. The thesis mainly focuses on the performance measurement of linear decision combiner in detecting primary users in a cognitive radio network.
This thesis is Open Access and may be downloaded by anyone.