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Top1. Introduction
Cognitive radio (CR) has been identified as a technology to enable dynamic spectrum access (DSA) which allows unlicensed users, called secondary users (SUs), to opportunistically use the temporarily unused channels of the licensed radio spectrum, called spectrum holes or white spaces. If this band becomes occupied by a licensed user, called a primary user (PU), the unlicensed user must leave the current band and move to another spectrum hole, avoiding interference with PUs. Cognitive radio ad hoc networks (CRAHNs) allow communication between cognitive users to be accomplished without the support of the fixed infrastructure or base station to meet the future demands of spectrum efficiency. Figure 1 shows the concept of a DSA. The SU dynamically uses the spectrum holes or white spaces that are not temporarily busy with the PUs, and the SU switches to a different frequency band after the current frequency band becomes occupied by the PU.
The routing of CRAHNs is a very important issue because it affects the performance in terms of delay and throughput of the entire network. The routing of a CRAHN is different from the routing in conventional ad hoc networks because it faces a number of challenges. One of the main challenges is that the spectrum availability is changed dynamically because a PU is moved randomly. Moreover, spectrum availability that can be used for communication may vary with time, frequency and power, as shown in Figure 1. In addition, QoS routing is not only measured by delay and throughput metrics as in the classical ad hoc networks, but the stability of the route is also a critical challenge. Therefore, designing a QoS routing protocol for CRAHNs is a more challenging task.
Figure 1. Concept of Dynamic Spectrum Access
Routing in CRAHNs is a very hot spot of research, and few researchers address the stability of quality of service as one of the routing metrics while calculating the optimal route to improve the performance of CRAHNs. One of the key routing metrics of CRAHNs is the route stability metric. It may be defined as function of a number of network parameters including node status, number of available channels, number of hops on the route, and channel activity. The channel activity of the route refers to the selection of the route with less PU activity (Habak et al., 2013). Route stability can be captured explicitly in the routing metric or implicitly (Youssef et al., 2014). The route stability of CRAHNs may be an atomic (single) metric or a global (multi) metric with other metrics (Youssef et al., 2014). The major aim of this paper is to develop an SWCETT routing protocol that combines the route stability metric with QoS metrics (such as delay and throughput) for CRAHN. The SWCETT routing protocol aims towards providing the most optimal route that satisfies the QoS requirements for SUs.
The reminder of this paper is organized as follows. Section 2 discusses the related work and research contribution. Sections 3 and 4 describe the system model and proposed approach. Section 5 describes the simulation results and discussion, and finally, section 6 concludes the work.