Peer-to-Peer Networking and Applications

, Volume 12, Issue 1, pp 280–290 | Cite as

An approach of robust power control for cognitive radio networks based on chance constraints

  • Zhiwei Zhao
  • Zhixin LiuEmail author
  • Panpan Wang
  • Xinping Guan


The changing and fluctuations of channel gains are inevitable in wireless communication. In this paper, a robust power control scheme for cognitive radio networks is proposed with consideration of uncertain channel gains. With the uncertainty, an optimal power control problem is formulated, which keeps the outage probability both of cognitive and primary users below the given threshold and maximizes the sum-utility of cognitive users. The chance-constraint robust approach is applied to transform the uncertain parameters into the determining setting, which is convexity of the outage probability constraints. In order to make the optimization problem solve facilely, the optimization problem is transformed to a convex problem by a suitable relaxation and the exponential transformations. The distributed power control algorithm based on Lagrange dual decomposition is proposed further. Numerical results show the convergence and effectiveness of the proposed chance-constraint robust power control algorithm. The sum of utility is improved and the energy consumption is reduced compared with some existing algorithms.


Cognitive radio networks Uncertain channel gain Power control Robust optimization 



This work is partly supported by National Natural Science Foundation of China under grant 61473247, the Natural Science Foundation of Hebei Province under grant F2017203140 and Science and Technology Research Projects in College of Hebei Province under grant QN2017416.


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer Science and TechnologyTangshan UniversityTangshanChina
  2. 2.Institute of Electrical EngineeringYanshan UniversityQinhuangdaoChina
  3. 3.School of Electronic, Information and Electrical EngineeringShanghai Jiaotong UniversityShanghaiChina

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