Telecommunications Science ›› 2023, Vol. 39 ›› Issue (2): 103-117.doi: 10.11959/j.issn.1000-0801.2023033

• Research and Development • Previous Articles     Next Articles

Secondary throughput maximization scheme for non-linear energy harvesting cognitive radio networks

Haijiang GE1, Ning JIA1, Kaikai CHI2, Yunzhi CHEN1   

  1. 1 College of Information Engineering, Hangzhou Vocational &Technical College, Hangzhou 310018, China
    2 School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China
  • Revised:2023-02-12 Online:2023-02-20 Published:2023-02-01
  • Supported by:
    The National Natural Science Foundation of China(61872322);Zhejiang Provincial Basic Public Welfare Research Project of China(LGG18F020005)

Abstract:

Aiming at a cognitive radio network (CRN) consisting of a pair of primary users and M pairs of secondary users, the secondary throughput maximization for CRN based on the non-linear energy harvesting model was studied.Specifically, in the case of considering secondary transmitter (ST) circuit power, the secondary throughput maximization (STM) problem with primary users’ throughput demands was first modeled as a non-linear optimization problem and then transformed into a convex optimization problem.Finally, a low-complexity algorithm combining the golden section and dichotomy was proposed.By applying this low-complexity algorithm, the optimal time allocation of the primary transmitter (PT)’s energy transmission and secondary users’ information transmission, and the optimal transmission power of PT were obtained.In addition, for the case of neglecting the ST circuit power, the convex property of the STM problem was first proved, and then a more efficient algorithm was designed to solve it.The simulation results show that compared with the equal time allocation method and the link gain priority method, the proposed design algorithm significantly improves the throughput of secondary users.

Key words: cognitive radio network, non-linear energy harvesting, secondary throughput maximization, low-complexity, convex optimization

CLC Number: 

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