Control Information Exchange In Cognitive Radio Ad Hoc Networks With Heterogeneous Spectrum

As an organic combination of the cognitive radio technology and Ad hoc networks, cognitive Ad hoc networks inherit some intrinsic features, e.g., multi-hop, distributed control mode, insufficient infrastructures, self-organization, of the traditional Ad hoc networks and some intelligent cognitive capacities, such as spectrum sensing, spectrum sharing, multi-channel switching, which can be used to improve the channel utilization ratio and integrate heterogeneous wireless networks. Therefore, cognitive Ad hoc networks can be generally applied in various kinds of communication scenarios.However, the inevitably evolving trend of the current licensed communication networks(such as macro-cell, micro-cell, pico-cell) is the network structure itself tends to be more diversified and the coverage shrinks, driving the unlicensed cognitive Ad hoc networks into more complex surroundings with spectrum availability very in time and location. That is to say, the nodes in different locations may access to different channels. To overcome the constraint of spectrum heterogeneity, cognitive ad hoc networks should exchange a specific amount of necessary control information within the network, so as for the sender and receiver to negotiate a suitable channel and proper chance, avoiding the interference from the licensed users and other cognitive users. Existing literatures have shown that categorizing the neighbor nodes with accessible bands similar into clusters can remarkably improve the control information exchange efficiency. Along the line of this, we place the focus on designing a complete set of cluster-based mechanisms for the control information exchange in cognitive Ad hoc networks with heterogeneous spectrum.First, to provide indispensable information for executing centralized clustering algorithms in this distributed network, this paper proposes a specially designed distributed information aggregation scheme for the network scenario with heterogeneous spectrum. By aggregating the topology and spectrum information of the entire network to a random but unique node rapidly and efficiently, this scheme can make the following procedure, namely node clustering, more robust and strengthen the information base for being able to further reduce the number of clusters and the cost of the inter-cluster control information exchange. Simulation shows, compared with existing data collection algorithms in heterogeneous spectrum case, the proposed scheme can decrease the desired amount of the control packets and shorter the time delay, efficiently reduce the consumption both in energy and time.Second, we turn the table by transforming the node clustering problem originally in heterogeneous spectrum case into multiple sub clustering problems in homogeneous spectrum cases. We then design two centralized clustering algorithms for the cognitive Ad hoc networks with heterogeneous spectrum: set covering problem based and maximal connectivity based clustering algorithms. Simulation shows that, compared with existing clustering algorithms in heterogeneous spectrum scenario, the proposed two algorithms yield less amount of clusters and better inter-cluster control information exchange efficiency without compromising the constrain of the preset minimal number of common channels in each cluster(i.e., robustness), achieving a better tradeoff between the robustness of clustering results and the inter-cluster control information exchange efficiency.Finally, based on the acquired clustering result, we then further propose a Hamiltonian cycle based intra-cluster control information exchange mechanism. In this mechanism, the intra and inter cluster control information exchange period in each cluster will be assigned with non-overlapped time slots, and then the ordered flow of the control information in such heterogeneous spectrum network can therefore be guaranteed. Simulation shows, compared with existing control information exchange mechanism in heterogeneous spectrum case, the proposed mechanism can efficiently reduce collisions between the control information packets when they are transmitted in cognitive Ad hoc networks and maintain the packet delivery delay relatively stable to adapt to various kinds of communication services. Meanwhile, such mechanism stays robust even when the accessible spectrum resources for cognitive node dynamically interfered by PN activity.