System Capacity Limits Introduced by Data Fusion on Cooperative Spectrum Sensing under Correlated Environments

Spectrum sensing, the cornerstone of the Cognitive Radio
paradigm, has been the focus of intensive research, from which the main
conclusion was that its performance can be greatly enhanced through
the use of cooperative sensing schemes. Nevertheless, if a proper design
of the cooperative scheme is not followed, then the use of cooperative
schemes will introduce some limitations in the network perceived
capacity. In this paper, we analyze the performance of a cooperative
spectrum sensing scheme based on Data Fusion, by measuring the
perceived capacity limits introduced by the use of Data Fusion on
cooperative sensing schemes. The analysis is supported by evaluation
metrics which accounts for the perceived capacity limits. The analysis is
performed along the data fusion chain, comparing several scenarios
encompassing different degrees of environment correlation between the
cluster nodes, number of cluster nodes, and sensed channel occupation
statistics. Through this study, we motivate that to maximize the perceived
capacity by the cooperative spectrum sensing, the use of data fusion
needs to be performed in a fractioned way, i.e., that the fusion must be
done between subsets of the nodes in a cluster.