# An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks
## 1 Introduction  
A wireless sensor network (WSN) is a network of a large number of densely deployed sensor nodes [1; 2] that are able to monitor various ambient conditions. Typically, a WSN operates using the unlicensed spectrum band. As time has gone by, the unlicensed band usage has become very crowded. Meanwhile, several field measurements showed low utilization on licensed spectrum bands [3; 4; 5]. The unbalanced situation makes the overall spectrum utilization low. To improve spectrum utilization and to accommodate users in the unlicensed spectrum band, an idea arose: allow unlicensed devices/users to transmit in the licensed band. In this environment, there are two types of users in the licensed bands: primary users (PUs) and secondary users (SUs). SUs need transmission devices capable of detecting PU transmissions, operating on a wide range of spectrum bands, and switching their operating spectrum/channel. Cognitive radio (CR) supports those capabilities and more. Since its introduction in 1999 [6], cognitive radio (CR) technology has received a lot of attention. The term \"cognitive radio\" first emerged in [7]; however, the definition of CR adopted here follows the thorough description by [PERSON] in [8] in agreement with the more general description by the FCC [9]. Many CR features and key implementation issues in existing wireless networks have been studied extensively [10; 11; 12; 13]. International standardization bodies are developing standards to guide the implementation of CR [14]. In this study, we are interested in the integration of CR in a wireless sensor network, i.e., a cognitive radio sensor network (CRSN) [15]. We believe that a wireless sensor network will be one ofthe fundamental elements in realizing the Internet of Things (IoT) [16] and a \"smarter world\" [17]. In CRSNs, the SUs are the sensor nodes. The main goal of implementing CR in WSNs is to improve the spectrum utilization of unlicensed spectrum bands [18; 19]. If the PUs share the licensed spectrum band with SUs, then the spectrum utilization would be increased [20]. This situation is called inter-spectrum sharing, which can be supported by setting a rule that the SUs must not interfere with the PU activity. However, SUs also have to share the vacant channels between them, that is intra-spectrum sharing. Intra-spectrum sharing can be achieved by applying an effective spectrum decision. A spectrum decision selects the operating channel of the SU among a number of possible channels [21]. The fundamental requirement of the spectrum decision is to select an operating channel that is reported vacant by the spectrum sensing [22; 23; 24]. When a single SU is considered, a spectrum decision may choose the \"best\" channel (highest signal-to-noise ratio, lowest bit error rate, and so forth) as its operating channel. However, in a CRSN network with multiple SUs, to select the best channel as the operating channel does not turn out to be the best solution. In this paper, we propose a spectrum decision scheme for CRSNs, called an energy-efficient game-theory-based spectrum decision (EGSD) scheme. In the proposed work, game theory is applied to the spectrum selection algorithm because it considers the interactions between multiple decision-makers (in this case, the SUs). However, a spectrum selection algorithm alone is not sufficient for a CRSN. The proposed spectrum decision scheme contains not only two spectrum selection algorithms but also a number of supporting algorithms. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. More specifically, we present: (1) a spectrum decision scheme for a CRSN; (2) two types of spectrum decision algorithm, i.e., random selection and game-theory-based selection; and (3) simple yet effective supporting algorithms for clustering, spectrum sharing, and spectrum access.