| With the rapid development of Internet of things and wireless communication technology,hundreds of millions terminals(mainly sensors)are connected to the Internet and growing at an annual rate of 21%.The limited battery becomes a constraint to expand the breadth and depth of the application.How to ensure energy-limited nodes to work sustainably is an urgent problem to be solved to achieve the vision of the Internet of things.The WPT could provide energy replenishment for nodes with long-distance.Therefore,the WPT has become an effective means to solve the problem of limited life for the sensors,with which the WRSNs can be charged by radio frequency signals.With good line-of-sight channel and excellent maneuverability,the UAV can improve the energy efficiency,effectively.In addition,as an important resource of energy-constrained networks,the power allocation affects the network performance,directly.This dissertation studies the performance and power allocation of UAV-Enabled WRSNs based on wireless charging.The main researches are as follows:(1)Aiming at the path planning problem of UAV-Enabled WRSNs based on wireless charging,an optimization model for minimizing the mission time of UAV is constructed.Meanwhile,a path planning algorithm is proposed,which manly includes three sub-algorithms.Firstly,a clustering algorithm based on neighbor nodes and charging radius is proposed for randomly distributed nodes.Then,an anchor selection strategy named NEAS is proposed which is considering the residual energy and clusters.Thus,the optimization problem is transformed into a NP-hard TSP.Finally,the path planning algorithm of UAV based on genetic algorithm is proposed.Compared with the basis schemes,the UAV mission time is effectively reduced with the same energy consumption.(2)Aiming at the performances for the UAV-Enabled wireless relay network,a closedform model of system throughput and outage probability with AF and DF protocol is derived under the modes of delay limitation and delay tolerance.Firstly,the SNR at the destination of the AF protocol and the DF protocol are derived,respectively.Moreover,the outage probability in the delay-constrained transmission mode is obtained.Secondly,the throughput with the both protocols in delay-limited transmission mode is obtained,respectively.And the analytical expression of ergodic capacity in delay-tolerant transmission mode is derived.Finally,the correctness of the theoretical derivation is verified by Monte-Carlo simulations,and the influences of various system parameters on the performances are analyzed.The results show that DF protocol has lower outage probability and higher throughput than AF protocol.(3)Aiming at UAV-Enabled wireless charging relay network,the model of minimizing the outage probability under the total power constraint and the model of minimizing the total power under outage probability constraints are constructed.The optimal power distribution method of UAV transmission power and source transmission power is proposed.Firstly,the model of minimizing the outage probability under the total power constraint is constructed.The analytical expression is obtained for the non-diversity gain system;for the diversity gain system,the relationship between UAV transmit power and source transmit power along with the optimal power allocation method are obtained.Then,the model of minimizing the total power under outage probability constraints is constructed,and the closed-form expression of the power allocation strategy is obtained for the non-diversity gain system.For the diversity gain system,the optimization problem is not convex and is not suitable for convex optimization.A dimensionality reduction method based on the power relationship between the source and the relay is proposed to reduce the complexity.Finally,the simulation verifies he optimal power allocation algorithm proposed can effectively reduce the outage probability of the system and improves the reliability of the system. |
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