a b s t r a c tCognitive radio networks (CRNs) promise to be the next generation of the key enabling technology that enables dynamic spectrum access (DSA). The channel assignment (CA) problem is one of the most important issues in CRNs, with the objective of satisfying the interference constraints, and maximizing the number of nodes with channels assigned. In this paper, our goal is to design highly-efficient and localized protocols for CA. In addition, we want to maximize node connectivity after CA, which is important for packet delivery. To this end, we design two basic algorithms and an advanced algorithm framework. Within this framework, we can change the edge priority in CA to meet different requirements. Simulation results show that the proposed framework is fast (two rounds of communication among nodes, regardless of network size) and outperforms an existing method.

The channel assignment problem is one of the most important issues in cognitive radio networks (CRNs). Under a SINR-driven model, we consider channel assignments in a network using dynamic source routing (DSR). In this unicasting model, channel assignments are conducted in a relatively small scale of nodes, which are on the chosen route. In addition, we can make use of the route reply (RREP) message in DSR to estimate the SINR and the maximum data transmission rate of nodes on the chosen route. In this way, the source node can conduct the channel assignment in a more efficient way. We propose two algorithms for the single route and multi-route channel assignments, where the multi-route scheme uses alternative nodes to help transmitting. We give a complexity analysis of two algorithms and an extension of reducing complexity for the multi-route channel assignment algorithm. Finally, we conduct simulations of our two algorithms under networks with different densities and show that the performance of our algorithms is efficient.Index Terms-channel assignment, cognitive radio networks, dynamic source routing, piggyback, SINR estimation.

Abstract-The advantages of virtual backbones have been proven in wireless networks. In cognitive radio networks (CRNs), virtual backbones can also play a critical role in both routing and data transport. However, the virtual backbone construction for CRNs is more challenging than for traditional wireless networks because of the opportunistic spectrum access. Moreover, when no common control channel is available to exchange the control information, this problem is even more difficult. In this paper, we propose a novel approach for constructing virtual backbones in CRNs, without relying on a common control channel. Our approach first utilizes the geographical information to let the nodes of a CRN self-organize into cells. Next, the nodes in each cell form into clusters, and a virtual backbone is established over the cluster heads. The virtual backbone is then applied to carry out the end-to-end data transmission. The proposed virtual backbone construction approach requires only limited exchange of control messages. It is efficient and highly adaptable under the opportunistic spectrum access. We evaluate our approach through extensive simulations.

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