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Volume 46 Issue 1
Jan.  2024
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XU Yongjun, FU Jiajin, HUANG Qiong, HUANG Dong. Robust Secure Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Multi-antenna Communication Systems[J]. Journal of Electronics & Information Technology, 2024, 46(1): 165-174. doi: 10.11999/JEIT221554
Citation: XU Yongjun, FU Jiajin, HUANG Qiong, HUANG Dong. Robust Secure Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Multi-antenna Communication Systems[J]. Journal of Electronics & Information Technology, 2024, 46(1): 165-174. doi: 10.11999/JEIT221554

Robust Secure Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Multi-antenna Communication Systems

doi: 10.11999/JEIT221554
Funds:  The National Natural Science Foundation of China (62271094), The Scientific and Technological Research Program of Chongqing Municipal Education Commission (KJZD-K202200601), Special support for Chongqing Postdoctoral Research Project (2021XM3082)
  • Received Date: 2022-12-16
  • Rev Recd Date: 2023-01-15
  • Available Online: 2023-02-04
  • Publish Date: 2024-01-17
  • To solve the problem of low security and poor transmission quality in cellular communication systems caused by eavesdroppers, obstacles and channel uncertainties, a robust secure resource allocation algorithm for Intelligent Reflecting Surface (IRS)-assisted multi-antenna communication systems is proposed. Firstly, a robust resource allocation problem with bounded channel uncertainties is formulated by jointly optimizing the active beam of the base station, the passive beam of the IRS, meanwhile the secure rate constraint of legitimate users, the maximum transmit power constraint and the phase shift constraint of the IRS are considered. Then, the original non-convex problem with parametric perturbation is transformed using S-procedure, successive convex approximation, alternating optimization and penalty function to obtain a deterministic convex optimization problem that can be solved directly. Finally, an iteration-based robust energy efficiency maximization algorithm is proposed. Simulation results show that the proposed algorithm has good energy efficiency and strong robustness.
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