Optimal Resource Allocation for Downlink OFDM-Based Cognitive Radio Networks
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2017 IEEE. In this paper, we study the downlink resource allocation (RA) problem in orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) networks. Our goal is to maximize the aggregated capacity of secondary users (SUs). In addition, the power of SUs is controlled to keep the interference introduced to primary users (PUs) under certain limits, which gives rise to a non-convex mixed integer non-linear programming (MINLP) optimization problem. In this paper, it is illustrated that the non-convex MINLP formulation admits a special structure and the optimal solution can be always achieved using standard convex optimization techniques under a general and practical assumption. In particular, the subgradient method is adopted to address the problem in the dual domain. The effectiveness of the proposed algorithms is verified by simulations.
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2017 International Symposium on Networks, Computers and Communications (ISNCC)