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urrent wireless networks are based on a fixed spectrum assignment policy that is regulated by governmental agencies. Although spectrum is licensed on a long-term basis over vast geographical regions, recent research has shown that significant portions of the assigned spectrum are utilized, leading to waste of valuable frequency resources [1]. To address this critical problem, the FCC recently approved the use of unlicensed devices in licensed bands. Toward this end, cognitive radio (CR) technology is envisaged that enables the identification and use of vacant spectrum, known as spectrum hole or white space [1]. In this article we focus on the challenges faced in CR ad hoc networks (CRAHNs), which do not have infrastructure support and must rely on local coordination for different CR functionalities.Since most of the spectrum is already assigned, a key challenge is to share the licensed spectrum without interfering with the transmission of other licensed users (also known as primary users or PUs). If this band is found to be occupied by a licensed user, the CR user moves to another spectrum hole to avoid interference. In CRAHNs the distributed multihop architecture, dynamic network topology, diverse quality of service (QoS) requirements, and time and location varying spectrum availability are some of the key factors that must be considered in network design. These challenges necessitate novel design techniques that simultaneously address a wide range of communication problems spanning several layers of the protocol stack.In CRAHNs CR users are mobile and can communicate with each other in a multihop manner on both licensed and unlicensed spectrum bands, as shown in Fig. 1a. Furthermore, due to the lack of central network entities, CRAHNs necessitate each CR user having all the spectrum related CR capabilities, and determining its actions based on local observation, leading to distributed operation [2]. In order to adapt to the dynamic spectrum environment, the CRAHN requires spectrum-aware operations, which form a cognitive cycle [1]. As shown in Fig. 1b, the steps of the cognitive cycle consist of four spectrum management functions: spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility. To implement CRAHNs, each function needs to be incorporated into the classical layering protocols, as shown in Fig. 2. The following are the main features of spectrum management functions:• Spectrum sensing: A CR user should monitor the available spectrum bands, capture their information, and then detect spectrum holes. Spectrum sensing is a basic functionality in CR networks, and hence closely related to other spectrum management functions as well as layering protocols to provide information on spectrum availability. • Spectrum decision: Once the available spectra are identified, it is essential that CR users select the best available band according to their QoS requirements [2]. Especially in CRAHNs, spectrum decision involves jointly undertaking spectrum selection and route formation.• Spectrum sharing: ...

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Abstract-Spectrum sensing is the key enabling technology for cognitive radio networks. The main objective of spectrum sensing is to provide more spectrum access opportunities to cognitive radio users without interfering with the operations of the licensed network. Hence, recent research has been focused on the interference avoidance problem. Moreover, current radio frequency (RF) front-ends cannot perform sensing and transmission at the same time, which inevitably decreases their transmission opportunities, leading to the so-called sensing efficiency problem. In this paper, in order to solve both the interference avoidance and the spectrum efficiency problem, an optimal spectrum sensing framework is developed. More specifically, first a theoretical framework is developed to optimize the sensing parameters in such a way as to maximize the sensing efficiency subject to interference avoidance constraints. Second, in order to exploit multiple spectrum bands, spectrum selection and scheduling methods are proposed where the best spectrum bands for sensing are selected to maximize the sensing capacity. Finally, an adaptive and cooperative spectrum sensing method is proposed where the sensing parameters are optimized adaptively to the number of cooperating users. Simulation results show that the proposed sensing framework can achieve maximum sensing efficiency and opportunities in multi-user/multi-spectrum environments, satisfying interference constraints.

Abstract-Cognitive radio (CR) networking achieves high utilization of the scarce spectrum resources without causing any performance degradation to the licensed users. Since the spectrum availability varies over time and space, the infrastructure-based CR networks are required to have a dynamic inter-cell spectrum sharing capability. This allows fair resource allocation as well as capacity maximization and avoids the starvation problems seen in the classical spectrum sharing approaches. In this paper, a joint spectrum and power allocation framework is proposed that addresses these concerns by (i) opportunistically negotiating additional spectrum based on the licensed user activity (exclusive allocation), and (ii) having a share of reserved spectrum for each cell (common use sharing). Our algorithm accounts for the maximum cell capacity, minimizes the interference caused to neighboring cells, and protects the licensed users through a sophisticated power allocation method. Simulation results reveal that the proposed inter-cell spectrum sharing framework achieves better fairness and higher network capacity than the conventional spectrum sharing methods.

Abstract-Cognitive radio (CR) networks have been proposed as a solution to both spectrum inefficiency and spectrum scarcity problems. However, they face several challenges based on the fluctuating nature of the available spectrum, making it more difficult to support seamless communications, especially in CR cellular networks. In this paper, a spectrum-aware mobility management scheme is proposed for CR cellular networks. First, a novel network architecture is introduced to mitigate heterogeneous spectrum availability. Based on this architecture, a unified mobility management framework is developed to support diverse mobility events in CR networks, which consists of spectrum mobility management, user mobility management, and intercell resource allocation. The spectrum mobility management scheme determines a target cell and spectrum band for CR users adaptively dependent on time-varying spectrum opportunities, leading to increase in cell capacity. In the user mobility management scheme, a mobile user selects a proper handoff mechanism so as to minimize a switching latency at the cell boundary by considering spatially heterogeneous spectrum availability. Intercell resource allocation helps to improve the performance of both mobility management schemes by efficiently sharing spectrum resources with multiple cells. Simulation results show that the proposed method can achieve better performance than conventional handoff schemes in terms of both cell capacity as well as mobility support in communications.Index Terms-Cognitive radio, spectrum pool, handoff, intercell resource allocation, spectrum mobility management, user mobility management.