Issue No. 10 - Oct. (2012 vol. 11)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TMC.2012.33
Sisi Liu , University of Arizona, Tucson
Loukas Lazos , University of Arizona, Tucson
Marwan Krunz , University of Arizona, Tucson
Cognitive radio networks (CRNs) involve extensive exchange of control messages, which are used to coordinate critical network functions such as distributed spectrum sensing, medium access, and routing, to name a few. Typically, control messages are broadcasted on a preassigned common control channel, which can be realized as a separate frequency band in multichannel systems, a given time slot in TDMA systems, or a frequency hopping sequence (or CDMA code) in spread spectrum systems. However, a static control channel allocation is contrary to the opportunistic access paradigm. In this paper, we address the problem of dynamically assigning the control channel in CRNs based on time- and space-varying spectrum opportunities. We propose a cluster-based architecture that allocates different channels for control at various clusters in the network. The clustering problem is formulated as a bipartite graph problem, for which we develop a class of algorithms that provide different tradeoffs between two conflicting factors: number of common channels in a cluster and the cluster size. Clusters are guaranteed to have a desirable number of common channels for control, which facilitates for graceful channel migration when primary radio (PR) activity is detected, without the need for frequent reclustering. We perform extensive simulations that verify the agility of our algorithms in adapting to spatial-temporal variations in spectrum availability.
Clustering algorithms, Bipartite graph, System-on-a-chip, Heuristic algorithms, Frequency control, Availability, Silicon, clustering., Dynamic spectrum networks, control channel assignment, cognitive radios, bipartite graphs
L. Lazos, M. Krunz and S. Liu, "Cluster-Based Control Channel Allocation in Opportunistic Cognitive Radio Networks," in IEEE Transactions on Mobile Computing, vol. 11, no. , pp. 1436-1449, 2012.