Research On Technology Of Scheduling Strategies In Energy Harvesting Networks

Energy harvesting network is a means of powering wireless electronic devices by scavenging many low grade ambient energy sources such as environmental vibrations,thermal,solar,wind and radiation and their conversion into useable electrical energy.Energy harvesting networks are therefore potentially attractive as replacements for wireless sensor nodes,implanted or wearable devices,mobile terminal equipment and so on.They also hold the promise of enabling the self-sustaining of network devices,widening the scope of network deployment,perlonging the lifetime of equipment and reducing operation and maintenance costs.System operation planning and design in energy harvesting network is a key issue in its development and application progress.The system operation planning and design need to consider the system energy harvesting status,network node device status,communication environment and so on,and aims to achieve the balance between system performance and energy consumption,energy transmission and information transmission under the constraints of energy collection,energy consumption balance,throughput,security rate and so on.Based on scenario generation technology,uncertainty theory,convex optimization and mathematical analysis,this paper studies the related issues of scheduling strategies in energy harvesting network.This study will provide valuable theoretical reference and technical means to promote the deployment and application of energy harvesting network.The main research contents are as follows:1)Most of the energy harvesting networks use the analytical probability distribution function to describe the energy harvesting process,which can not accurately simulate the actual situation because the lack of authenticity.We propose an energy harvesting networks simulation method based on scenario generation in this paper.Firstly,based on the historical data of the harvested energy,the method does not need to set a probability distribution function in advance,and uses optimal scenario reduction technology to generate representative scenarios in single period.Secondly,it uses homogeneous simulated annealing algorithm to generate daily scenario sequences,so that can accurately capture the random characteristics in energy harvesting networks.Taking the actual wind power data as an example,the accuracy and stability of the method are verified by comparison with the real data.Then we cite an instance to optimize network throughput,the optimal solution and data analysis showed the method based on scenario generation is feasible and effective in energy harvesting networks.2)The energy harvesting process has great volatility and uncertainty,the traditional analytical method based on probability distribution function to describe the energy collection process,can not accurately simulate the actual situation,resulting in higher depletion probability of nodes,the reliability cannot be guaranteed as a result.For this,the reliability of the energy harvesting nodes is defined,represented with the degree of normal operation,respectively set up the node reliability models with no battery and infinite battery;as an example for maximum node achievable rate,the uncertain multilevel programming model based on node reliability is put forward,then the network efficiency is improved under the premise of ensuring node reliability;an energy average allocation algorithm(EAA)is proposed and the upper bound of competitive ratio of the algorithm is proved theoretically.Finally,the actual wind power data is taken as an example to verify the feasibility and effectiveness of the proposed model and method.3)Wireless energy harvesting technique has emerged as a fascinating solution to extend the lifetime of energy constrained networks.However,most of the current researches focus on single antenna network systems,and linear energy harvesting model cannot describe the system harvesting process accurately.Therefore,the multi-user multiple input and multiple output cognitive wireless powered communication system based on energy harvesting network is put forward.With the non-linear energy harvesting model,we establish system throughput optimization model under overlay and underlay scenarios respectively.The problems are generally jointly concave due to the coupled variables and non-linear constraints.To overcome the non-convexity,we convert the problems into equivalent convex forms,and then identify the solutions by applying the Lagrange dual methods.In addition,we also obtain the optimal energy and information transmit covariance matrices respectively,and the optimal time allocation factors.All the solutions’optimality are proved by mathematical methods theoretically.Finally,the effectiveness and performance of the proposed algorithms are verified based on the actual wind energy harvesting data.Simulation results show that,the optimal algorithm can achieve better average system throughput than the average power allocation algorithm,and the algorithm converges steadily after a finite number of iterations.4)The robust secure beamforming design for energy harvesting cognitive radio network with SWIPT is studied,where the secondary users are coexisted with multiple primary users and multiple energy harvesting nodes.In order to ensure secure communications and energy harvesting,a robust and secure artificial noise-aided beamforming and power allocation problem under imperfect CSI is proposed.Based on the bounded CSI error model and the probabilistic CSI error model,the transmission power minimization problem and the max-min fairness energy harvesting problem are established respectively.Since the above problems are non-convex,one-dimensional search algorithms separately based on Bernstein inequality under bounded CSI error model and S-process under probabilistic CSI error model are propose.The results show that the optimal robust and secure beamforming can be achieved under the bounded CSI error model,and the sub-optimal beamforming solution can be obtained under the probabilistic CSI error model.Under max-min fairness criterion,the balance between the security rate of secondary users and the energy harvesting at the energy harvesting nodes is achieved.Finally,the work of this paper is summarized,and the research and development of energy harvesting network are prospected.