Abstract
In order to improve the effective utilization of available resources in the traditional wireless network, this paper studies the optimization of resource allocation (RA) in the underlay cognitive radio network (CRN). Our goal is to maximize the sum rate of the whole system (e.i., primary users (PUs) and secondary users (SUs)), taking into account the constraints of interference temperature (IT) and minimum rate, and the Quality of Service (QoS) guarantees. A heuristic algorithm is proposed to solve the non-convex non-linear programming optimization problem. Theoretical analysis and simulation results show that this algorithm can effectively reduce the power interference to the PUs, maximize the transmission rate of PUs and SUs, and improve resource utilization of the CRN.
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Acknowledgments
This work is supported in part by National Natural Science Foundation of China (No. 61379005) and (No. 61771410), 2016 Key base of tourism and scientific research of Sichuan Provincial Tourism Administration (No. ZHZ16-02), and 2017, 2018 Artificial Intelligence Key Laboratory of Sichuan Province (No. 2017RYY05, No. 2018RYJ03), and 2017 Horizontal Project (No. HX2017134), and 2015 Teaching Reform Project (No. B11605035), and 2018 Postgraduate Innovation Fund Project by Southwest University of Science and Technology (No. 18ycx115).
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He, X., Jiang, H., Song, Y., Xiao, H. (2018). Optimal Resource Allocation for Underlay Cognitive Radio Networks. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11066. Springer, Cham. https://doi.org/10.1007/978-3-030-00015-8_31
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DOI: https://doi.org/10.1007/978-3-030-00015-8_31
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