Research On Secure Energy Efficiency And Available Energy Planning In SWIPT Networks

In the Simultaneous Wireless Information and Power Transfer(SWIPT)network,this thesis studies the energy efficiency maximization and secure energy minimization problem in the downlink Multiple-Input Sigle-Output(MISO)network respectively.Finally,we solved the constructed non-convex optimization problem based on two improved swarm intelligence optimization algorithms.Firstly,this thesis proposes a new energy receiving mechanism under the nonlinear energy receiving model,which effectively avoids the problem that the receiver enters the saturation region and solves the problem of false output during the energy conversion process.Considering that the transmitter can only obtain the static distribution information of the channel in reality,to obtain the dynamic relationship between information transmission and energy consumption,this thesis adopts the dynamic energy consumption model.Under the constraints of outage probability,total available power,and power available to authorized users,an optimization problem to maximize system energy efficiency is designed.Since the objective function is in fractional form and the optimization problem is not convex,this thesis proposes an improved Teaching-Learning-Based Optimization(TLBO).Within the theoretical framework of the improved TLBO algorithm,an optimization problem with the objective function of maximizing the energy efficiency of the system is designed by jointly optimizing the beamforming vector,the energy split ratio and the transmission rate.Simulation experiments show the effectiveness of the proposed energy efficiency optimization scheme and the reliability of the proposed algorithm.Secondly,in the multi-user downlink MISO network,artificial noise(AN)is embedded into the transmit signals to prevent the authorized user information from being intercepted by the energy receiving users.The secrecy energy resources allocation problem is formulated by jointly optimizing the beamforming vector of information transmission,the power split ratio of idle users and the covariance matrix of artificial noise.To solve the constructed non-convex optimization problem,an improved Whale Optimization Algorithm(WOA)is proposed,which minimizing the system energy consumption under the premise of enhancing the balance between the exploration phase and the development phase.The simulation results show that the proposed energy optimization problem of confidential information has certain practical significance under the nonlinear receiving model,and the improved WOA algorithm has better network performance than other swarm intelligence algorithms.