## 1 Introduction  
Spectrum scarcity in the fixed allocation policy is one of the main obstacles to the deployment of existing wireless communication systems and services, and to the development of new ones. With the advent of the cognitive radio (CR) paradigm [1], cognition-inspired dynamic spectrum access [2] techniques come into action by exploring the underutilized portions of the spectrum in time and space, while causing no or minimum harm in the system that pays for using that portion of the spectrum. Among the many cognitive tasks that a CR can perform, spectrum sensing is the task of detecting holes in frequency bands licensed to primary wireless networks for opportunistic use by secondary cognitive radios. Although sensing can be performed by each secondary receiver in a non-cooperative fashion, cooperative spectrum sensing has been considered a possible solution for problems experienced by CR networks in a non-cooperative sensing situation, like receiver uncertainty, multipath fading, hidden terminals, and correlated shadowing. Among the existing spectrum sensing techniques [3], eigenvalue-based schemes are receiving a lot of attention [4; 5; 6], mainly because they do not require prior information on the transmitted signal, and, unlike in energy-detection, in some eigenvalue-based schemes the knowledge of noise variance is not needed either [6].  
Cooperative spectrum sensing can be classified as centralized and distributed, with the possibility of being relay-assisted [3] in both situations. In centralized cooperative sensing, data collected by each cooperating CR (e.g., received samples) are sent via a reporting control channel to a fusion center (FC), in a process called data-fusion. After the FC processes the data from the CRs, it decides upon the occupancy of the sensed channel. Centralized cooperative sensing can also be performed based on the hard decisions made by all cooperating CRs, in a process called decision-fusion. In this case, these decisions are combined at the FC using binary arithmetic before the final decision is arrived at. In both centralized schemes, the final decision is reported back to the CRs via a control channel, and an access algorithm takes place in the sequel. In distributed cooperative sensing, no FC exists and the final decision is iteratively reached by the cooperating CRs that communicate among themselves. In the case of relay-assisted cooperative sensing, a given CR may serve as a relay to forward the sensing information from one CR to another, for centralized or distributed operation.  
It is worth mentioning that the role of an FC in a centralized cooperative spectrum sensing can be assigned to a cluster-head in the context of clustered network topologies [7], which is the case of most wireless sensor networks (WSN). This clustering approach can be of particular value in large area networks, where the adoption of a single FC could increase prohibitively the control channel traffic and lead to inefficient spectrum utilization. This inefficiency can be caused by the distinctive spectrum occupancy in different regions of the network, which could be misled by large-area-based centralized decisions.