Today's wireless networks are characterized by a fixed spectrum assignment policy. However, a large portion of the assigned spectrum is used sporadically and geographical variations in the utilization of assigned spectrum ranges from 15% to 85% with a high variance in time. The limited available spectrum and the ine#ciency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum opportunistically. This new networking paradigm is referred to as NeXt Generation (xG) Networks as well as Dynamic Spectrum Access (DSA) and cognitive radio networks. The term xG networks is used throughout the paper. The novel functionalities and current research challenges of the xG networks are explained in detail. More specifically, a brief overview of the cognitive radio technology is provided and the xG network architecture is introduced. Moreover, the xG network functions such as spectrum management, spectrum mobility and spectrum sharing are explained in detail. The influence of these functions on the performance of the upper layer protocols such as routing and transport are investigated and open research issues in these areas are also outlined. Finally, the cross-layer design challenges in xG networks are discussed.

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Abstract—Wireless Mesh Networks (WMNs) are envisaged to extend Internet access and other networking services in personal, local, campus, and metropolitan areas. Mesh routers (MR) form the connectivity backbone while performing the dual tasks of packet forwarding as well as providing network access to the mesh clients. However, the performance of such networks is limited by traffic congestion, as only limited bandwidth is available for supporting the large number of nodes in close proximity. This problem can be alleviated by the cognitive radio paradigm that aims at devising spectrum sensing and management techniques, thereby allowing radios to intelligently locate and use frequencies other than those in the 2.4GHzISM band. These promising technologies are integrated in our proposed COgnitive Mesh NETwork (COMNET) algorithmic framework, thus realizing an intelligent frequency-shifting self-managed mesh network. The contribution of this paper is threefold: (1) A new approach for spectrum sensing is devised without any change to the working of existing de facto mesh protocols. (2) An analytical model is proposed that allows MRs to estimate the power in a given channel and location due to neighboring wireless LAN traffic, thus creating a virtual map in space and frequency domains. (3) These models are used to formulate the task of channel assignment within the mesh network as an optimization problem, which is solved in a decentralized manner. Our analytical models are validated through simulation study, and results reveal the benefits of load sharing by adopting unused frequencies for WMN traffic.

Cognitive radio networks have been proposed as a solution to both spectrum inefficiency and spectrum scarcity problems. However, they face to a unique challenge based on the fluctuating nature of heterogeneous spectrum bands as well as the diverse service requirements of various applications. In this paper, a spectrum decision framework is proposed to determine a set of spectrum bands by considering the application requirements as well as the dynamic nature of spectrum bands. To this end, first, each spectrum is characterized by jointly considering primary user activity and spectrum sensing operations. Based on this, a minimum variancebased spectrum decision is proposed for real-time applications, which minimizes the capacity variance of the decided spectrum bands subject to the capacity constraints. For best-effort applications, a maximum capacity-based spectrum decision is proposed where spectrum bands are decided to maximize the total network capacity. Moreover, a dynamic resource management scheme is developed to coordinate the spectrum decision adaptively dependent on the time-varying cognitive radio network capacity. Simulation results show that the proposed methods provide efficient bandwidth utilization while satisfying service requirements.

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. I.

We propose a distributed dynamic frequency allocation algorithm that achieves performance close to that of a centralized optimal algorithm. In our network model, nodes are grouped into a number of clusters. Each cluster chooses its transmission frequency band based on its knowledge of the interference that it experiences. The convergence of the proposed distributed algorithm to a sub-optimal frequency allocation pattern is proved. For some specific cases of spatial distributions of the clusters in the network, asymptotic bounds on the performance of the algorithm are derived and comparisons to the performance of optimal centralized solutions are made. These analytic results and additional simulation studies verify performance close to that of an optimum centralized frequency allocation algorithm. I.

Abstract — Spectrum sharing in open spectrum systems is a challenging problem, particularly since users experience dynamic spectrum availabilities that vary over time and location. In the absence of any centralize infrastructure, users coordinate their spectrum usage to support fair access of spectrum and avoid interference. One critical challenge is to construct an efficient signalling path in the presence of spectrum dynamics, where users exchange control and negotiation information reliably. In this paper we propose a distributed coordination protocol (HD-MAC) to construct an in-band control path without relying on the existence of a pre-assigned out-of-band control channel. In particular, we propose a distributed group formation to construct coordination path using local common channels, and a heterogeneity-aware ranking scheme to select channels for data transmissions. Extensive experimental results demonstrate the efficiency and reliability of the proposed approach. I.

Device coordination in open spectrum systems is a challenging problem, particularly since users experience varying spectrum availability over time and location. We propose a distributed coordination approach that handles spectrum heterogeneity without relying on the existence of a preassigned common control channel. Our approach carries potential to provide robust operation under network dynamics. While this approach can be implemented by upgrading the legacy protocol stack without modifying the MAC protocol, we also describe modifications to the MAC protocol that address spectrum heterogeneity and significantly improve system performance. Experimental results show that the proposed distributed coordination scheme outperforms the existing coordination schemes by 25-35% in throughput and provides 50% of delay reduction.

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A study by Federal Communication Commission shows that most of the spectrum in current wireless networks is unused most of the time, while some spectrum is heavily used. Recently dynamic spectrum access (DSA) has been proposed to solve this spectrum inefficiency problem, by allowing users to opportunistically access to unused spectrum. One important question in DSA is how to efficiently share spectrum among users so that spectrum utilization can be increased and wireless interference can be reduced. Spectrum sharing can be formalized as a graph coloring problem. In this report we focus on surveying spectrum sharing techniques in DSA networks and present four representative techniques in different taxonomy domains, including centralized, distributed with/without common control channel, and a real case study of DSA networks — DARPA neXt Generation (XG) radios. Their strengths and limitations are evaluated and compared in detail. Finally, we discuss the challenges in current spectrum