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Volume 46 Issue 2
Feb.  2024
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XU Yongjun, JIANG Siqiao, ZHANG Haibo, WANG Zhengqiang, ZHOU Jihua. Robust Secure Resource Allocation Algorithm for Cognitive Backscatter Communication with Hardware Impairment[J]. Journal of Electronics & Information Technology, 2024, 46(2): 652-661. doi: 10.11999/JEIT230117
Citation: XU Yongjun, JIANG Siqiao, ZHANG Haibo, WANG Zhengqiang, ZHOU Jihua. Robust Secure Resource Allocation Algorithm for Cognitive Backscatter Communication with Hardware Impairment[J]. Journal of Electronics & Information Technology, 2024, 46(2): 652-661. doi: 10.11999/JEIT230117

Robust Secure Resource Allocation Algorithm for Cognitive Backscatter Communication with Hardware Impairment

doi: 10.11999/JEIT230117
Funds:  The National Natural Science Foundation of China (62271094), The Scientific and Technological Research Program of Chongqing Municipal Education Commission (KJZD-K202200601), The China Postdoctoral Science Foundation (2022MD723725), The Sichuan Regional Innovation Cooperation Project (2022YFQ0017)
  • Received Date: 2023-03-01
  • Rev Recd Date: 2023-05-11
  • Available Online: 2023-05-18
  • Publish Date: 2024-02-29
  • To improve spectral efficiency, transmission robustness, and information security of backscatter communication networks, a robust secure resource allocation algorithm is proposed for cognitive backscatter communication networks with hardware impairments. Firstly, considering the constraints of the minimum secure rate of each cognitive backscatter user, transmission time, energy harvesting, and reflection coefficients, a multivariable coupled resource allocation problem with throughput maximization is established under bounded channel uncertainties and spectrum sensing errors. Secondly, the original problem is transformed into a convex problem by using a worst-case approach, successive convex approximation, alternating optimization, and an iteration-based robust resource allocation algorithm is proposed to solve it. Simulation results show that the proposed algorithm has better robustness by comparing it with the existing algorithms.
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