## 1 Introduction  
The unprecedented offer for the current explosive amount of new telecommunication services is among many benefits of the evolution of communication systems in the last decades. The improvements provided from older generations of mobile communication systems to its fifth generation (5G) and the advent of the Internet of things (IoT) [1], for instance, have allowed a significant increase in the users quality of service (QoS) and quality of experience (QoE) also driving the traditional concept of wireless communication to a new age in which everyone can connect to everything, everywhere, and at any instant [2]. Moreover, as wireless technologies are continuously under enhancement [3] and evolutions occur pretty fast, lots of new features, applicabilities, and solved problems become available all the time. Indeed, 5G and IoT were just born a few years ago, but even so, several academic research projects and companies are already researching the sixth generation (6G) of mobile communication systems around the world [4]. The above statements and statements in [3] indicate that the introduction of new technologies may occur soon, yet with the potential to revolutionize the existing ones. However, a drawback of the rapid evolution of communication systems is the lack of spectrum bands available to allocate such a large amount of new telecommunication services. That lack of spectrum resources is usually called spectrum scarceness. Spectrum scarceness can be understood as the result of the growth in demand for additional spectrum bands in the last decades. On the other hand, studies on literature show that although scarce, spectrum resources are also contradictorily underused [5]. According to these studies, the main reasons for spectrum underutilization are both (i) the procedure regarding the spectrum access that, in fact, gives access rights only to primary users for the contracted time-space domains, and (ii) the low utilization of these incumbents in accessing their spectrum bands in the contracted time-space domains. Consequently, regulatory agencies of spectrum access started considering a new spectrum access policy aiming at mitigating underutilization. In this new access policy, primary spectrum bands could opportunistically be used by non-incumbents or secondary users (SUs) if they find idle/vacant primary user (PU) bands. For that reason, the SUs have to be smart devices in order to find and use possibly vacant PU bands without causing harmful interference to PUs. Fortunately, the concept of spectrum sensing based on cognitive radios (CRs) has emerged as a promising solution to this problem since it is the act of sensing the spectrum seeking idle portions for opportunistic use. Thus, in the context of CR-based spectrum sensing, CRs are intelligent SUs capable of providing secondary access to vacant PU bands without causing harmful interference to PUs via spectrum sensing and then mitigating spectrum underutilization and scarceness. Spectrum sensing (SS) can be carried out by one CR, or SU, in non-cooperative spectrum sensing (nCSS) or by a group of collaborative SUs in cooperative spectrum sensing (CSS). CSS, however, is wider used due to more statistical power in detecting PU signals. One of the main advantages that give more detection performance to CSS is the spatial diversity of SUs in different geographical locations for sensing the spectrum. The spatial diversity in the positions of cooperating SUs allows the secondary network to overcome issues that nCSS generally cannot, like multipath fading, shadowing, hidden PU terminal problems, or a combination of these phenomena [6]. Additionally, CSS may be centralized, distributed, or relay-assisted [6]. In centralized CSS, SUs sense a target PU band and share some sensing information with a central node called fusion center (FC) via a control channel (CC) for making an occupation decision on its occupation state. This kind of information determines two possible fusion rules.