Spectrum Allocation In The Heterogeneous Cognitive Radio Networks

Currently, the contradiction between the spectrum resources constraint of the new wireless technology and the inefficient usage of the primary spectrum is becoming increasingly prominent. The Cognitive Networks technology can detect the idle spectrum resources and allocate them to the cognitive users efficiently, which therefore becomes a resolution to the contradiction described above.In this paper, it introduces the related technologies of Cognitive Radio and Cognitive Networks at fiest. Based on that, it introduces a network architecture, because for now no suitable architecture models of the heterogeneous cognitive radio networks are available. Specific details of each function module of this network architecture and a feasible network organization model for different scenarios are also described in this paper. Furthermore, based on the Graph Theory, it proposes two new algorithms to allocate spectrum resources according to either capacity or QoS priority. They address the problem that the usage requirement of the heterogeneous cognitive radio networks cannot be met by the existing algorithms mostly based on simple spectrum allocation abstraction and scenario analysis.Therefore, the main work of this paper is:(1) Introduced a network architecture of heterogeneous cognitive radio networks and proposed a network organization model. In this architecture, there are three layers: Application Service Layer, Core Network Layer and Wireless Access Layer. In Core Network Layer, all kinds of wireless networks are integrated into a systematic and unified network by means of Intelligent Control Nodes. The heterogeneous integration of the networks and the interconnections between the operators are further achieved by introducing function modules such as the Internetwork Coordination Module. The network organization model divides the heterogeneous cognitive radio networks into a number of different areas according to the factors like locations, barriers.etc, and shares spectrum in the same area. It also provides the application scenarios to study and validate the channel allocation algorithms.(2) Proposed an algorithm to allocate spectrum resources based on capacity(CC-RB), which aims to ensure the maximum network capacity. The algorithm recognizes the capacity differences among different channels, and allocates the channel which has the maximum capacity to the cognitive node. The simulation results proved that the proposed algorithm can significantly enhance the network capacity and fairness.(3) Proposed an algorithm to allocate spectrum resources based on QoS priority(QP-RB), which considers the different QoS requirements and divides the nodes into different priorities according to the hosted businesses. The algorithm defines three states for the networks, and sets up an evaluation model based on Bayesian Networks(BN) to achieve intelligent selection of prioritized nodes. In the channel allocation process, allocating channels to all the prioritized nodes firstly, and to the non-prioritized afterwards. The simulation results proved that the proposed algorithm can enhance the average node capacity, and the network capacity when there are a large number of nodes.