Distributed Matching Based Spectrum Allocation in Cognitive Radio Networks

In cognitive radio (CR) networks, due to the uncertainty of primary users' (PUs) traffic, there are vacant bandwidths that can be accessed by secondary users (SUs). Thus, this provides mutual benefit opportunities for both PUs and SUs. In this paper, the objective is to select the optimal channel utilization for maximizing the system utility. To solve the problem, we employ the matching theory as the mathematical framework to firm mutually beneficial relationships between PUs and SUs. In particular, we propose a distributed matching algorithm for many-to-one matching considering both SUs' and PUs' characteristics. Simulation results show that the proposed distributed algorithm achieves a performance close to the centralized method, and outperforms the greedy allocation in different scenarios.