| With the rapid advancement of 5th Generation Mobile Networks(5G)mobile communication commercialization,wireless characters such as high bandwidth,low delay,ultra-dense connection are also increasingly desired by people.At the same time,the broadcast characteristics of wireless information make the security of high-speed information transmission seriously threatened,the physical layer security is increasingly becoming the focus of research.The thesis mainly studies the algorithm optimization problem of Secure Energy Efficiency(SEE)in MIMO systems under Simultaneous Wireless Information and Power Transfer(SWIPT)and draws the following conclusions.First,to solve the SEE optimization problem in massive MIMO system based on linear Energy Harvesting(EH),the thesis combines Base Station(BS)transmit power,BS power allocation factor and user power allocation factor to maximize the minimum user's SEE.Firstly,it analyzes the model of the massive MIMO system when the eavesdropper exists.Secondly,the objective function is established according to the system model.Then,the optimization algorithm that fractional programming and Difference of two Concave functions(DC)programming to solve the objective function,and proposed the maximum-minimum user's SEE algorithm.Finally,the algorithm proposed in this thesis is compared with the maximum users' system SEE algorithm and the maximum secure rate algorithm to verify the effectiveness of the proposed algorithm.Simulation results show that the proposed algorithm has good convergence and better performance than the maximum users' system SEE algorithm and the maximum secure rate algorithm.Second,based on the analysis of the nonlinear EH system model,to solve the nonlinear EH massive MIMO system SEE optimization problems,the thesis considers the nonlinear EH model,linear EH model and no Artificial Noise(AN)nonlinear EH model to the system SEE optimization problems.First of all,the thesis analyzes the working mechanism of the nonlinear model of EH.Secondly,under the conditions of power constraint and energy constraint,the objective function based on the nonlinear EH model is established.Then,DC programming and fractional programming were used to solve the massive MIMO system SEE optimization problems based on thenonlinear EH model,and compared with the SEE optimization algorithm under the linear EH model and no AN nonlinear EH model.Simulation results show that the SEE optimization algorithm under the nonlinear EH model has better performance than the linear EH model and the no AN nonlinear EH model. |
