Secrecy Rate Maximization Algorithm for Intelligent Reflecting Surface Assisted Wireless Energy Transmission
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摘要: 为了减少窃听者对合法接收者的信息接收影响和窃听者的有用信息接收量，该文研究利用智能反射表面(IRS)来实现无线供电通信网络(WPCN) 中窃听端处的波束抵消。首先在传输能量的同时进行窃听检测，IRS根据合法用户的能量状态选择是否采取防窃听模式，然后在存在窃听的情况下，研究了窃听信道完美和不完美状态下系统的保密率最大化问题。分析表明，这一最大化问题是相移、功率分配、时间分配的多变量耦合非凸问题，可以采用分步优化、变量替换和S-Lemma等方法进行求解。仿真结果表明，与基准算法相比，所提算法提升了保密率，当智能反射表面元件数为80时保密率提升了44%，发射功率为40 dBm时保密率提升了34%。Abstract: To reduce the influence of eavesdropper on the information reception of the legitimate receiver and the amount of useful information received by the eavesdropper, the beam cancellation at the eavesdropper in Wireless Powered Communication Network (WPCN)with Intelligent Reflecting Surface (IRS) is studied in this paper. Firstly, eavesdropping detection is carried out together with energy transmission, IRS chooses whether to adopt anti-eavesdropping mode according to the energy state of legitimate users. Then, under the conditions of eavesdropping, the maximization of system secrecy rate is studied for perfect and imperfect eavesdropping channel respectively. The maximization algorithm is a multi-variable coupling non-convex problem composing of phase shift and power distribution and time distribution, which is solved by methods such as stepwise optimization, variable substitution and S-Lemma. The simulation results show that, compared with the benchmark algorithm, the proposed algorithm improves the security rate. When the number of IRS elements is 80, the security rate is increased by 44%, and when the transmit power is 40 dBm, the security rate is increased by 34%.
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