研究了包含多个多天线窃听者的多输入多输出无线携能系统.在窃听者信道状态信息不精准的情况下，通过联合设计波束成形矩阵、人工噪声协方差矩阵和功率分配比，在满足发射功率约束和能量收获约束的条件下，最大化系统最差情况保密能量效率.基于分式理论，将原非凸问题转化为减式形式的等效优化问题.通过新颖的等效变换，解决了多个优化变量之间的耦合问题，避免了交替优化.借助于S-procedure和一阶泰勒级数展开，将难以处理的非凸问题转化为凸问题.提出了基于Dinkelbach方法的两级优化迭代算法且仿真结果验证了该算法的有效性和收敛性.
This paper investigates simultaneous wireless information and power transfer in multiple-input-multiple-output system consisting of multiple multi-antenna eavesdroppers. In the case that the channel state information of the eavesdroppers can not be accurately obtained, the objective is to maximize the worst-case secrecy energy efficiency by jointly designing the beamforming matrix, artificial noise covariance matrix and power splitting ratio subject to transmit power constraint and energy harvest constraint. Based on fractional theory, the original non-convex problem is transformed into an equivalent optimization problem in subtractive form. By means of novel equivalent transformation, the problem of coupling between multiple optimization variables is solved and then the alternating optimization is avoided. With the aid of S-procedure and first order Taylor series expansion, the non-convex problem is transformed into a convex one. Based on Dinkelbach method, a two-level optimization iterative algorithm is proposed and simulation results are provided to show the effectiveness and convergence of the proposed algorithm.
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