Matching Theory for Channel Allocation in Cognitive Radio Networks

Abstract

For a cognitive radio network (CRN) in which a set of secondary users (SUs) competes for a limited number of channels (spectrum resources) belonging to primary users (PUs), the channel allocation is a challenge and dominates the throughput and congestion of the network. In this paper, the channel allocation problem is first formulated as the 0-1 integer programming optimization, with considering the overall utility both of primary system and secondary system. Inspired by matching theory, a many-to-one matching game is used to remodel the channel allocation problem, and the corresponding PU proposing deferred acceptance (PPDA) algorithm is also proposed to yield a stable matching. We compare the performance and computation complexity between these two solutions. Numerical results demonstrate the efficiency and obtain the communication overhead of the proposed scheme.