Approximating Common Control Channel Problem in Cognitive Radio Networks

Abstract

Cognitive radio networks (CRNs) involve an extensive exchange of control messages to coordinate spectrum sensing, medium access, routing, etc. Static control channel allocation uses preassigned common control channel (CCC) contrary to the opportunistic access paradigm. We propose a k-hop clustering scheme for the optimal CCC assignment problem (k-CCCP) for CRNs. We prove that the k-CCCP problem is NP-hard (nondeterministic polynomial-time hard) by reduction using minimum dominating set problem. We also found that the k-CCCP problem is approximable hard. We propose a ln Δ approximation algorithm for the k-CCCP problem, where Δ is the largest cardinality among all khop neighborhood in a CRN. To account for primary user dynamics, we propose a distributed ranking algorithm for the k-CCCP problem with message complexity O(nδk), where n, δ, and k are number of nodes, the largest node degree, and hop parameter, respectively. To address the negative effect of multihop clustering, we also propose a mechanism to find the optimal k value in multihop clustering. For performance comparison, extensive simulations are performed and the results show that our proposed scheme outperforms with the competitive schemes.