Deployment Strategies Of Sensors And Chargers In Radio Frequency Powered Networks

Due to the breakthrough in radio frequency(RF)power transfer technology,sensor nodes with RF energy converting unit can harvest predictable and stable energy provided by wireless chargers.The problems of sensor and charger deployment are two critical issues in RF powered networks.For static sensor nodes deployed in the surrounding environment for target detection,rational planning of sensor placement and charging/sensing schedules according to the distribution of wireless chargers and surveillance spots is an effective way to improve the overall surveillance quality.For mobile sensor nodes carried by users,service providers can deploy wireless chargers to provide wireless charging service.Rational planning of chargers’ locations and transmit power levels according to users’ tempo-spatial distribution can maximize service providers’ revenue.The major work of this dissertation is as follows:For application scenario in which RF powered network is used for target dectection,a sensor deployment strategy is proposed based on fusion dectection model to maximize overall dectection quality.Firstly,simultaneous sensor placement and charging/sensing scheduling problem for fusion-based detection is formulated as a constrained optimization problem.The problem is further transformed into an equivalent problem that is proved to be NP-complete for easier tractability.After analyzing the impact of fusion radius,the upper bound of fusion radius is proved.Two greedy heuristic algorithms,Joint Optimization Greedy Algorithm with Fixed Fusion Radius(JOGA-FFR)and Joint Optimization Greedy Algorithm with Dynamic Fusion Radius(JOGA-DFR)based on fixed and dynamic fusion radiuses respectively,are proposed to solve the problem.Finally,the proposed algorithms are validated through extensive numerical simulations as well as simulations based on real data traces collected from a vehicle detection experiment.The results show that,the two proposed algorithms always outperform Two-Stage Greedy Algorithm(TSGA),an algorithm that optimizes sensor placement and scheduling separately,in all the simulation scenarios,and are near optimal in small-scale networks.JOGA-DFR outperforms JOGA-FFR under certain specific sensing model settings,but more often has a comparable performance with JOGA-FFR.JOGA-FFR is thus more recommended for its lower complexity.For application scenario of wireless charging service for mobile sensors nodes carried by users,a charger deployment strategy is proposed to maximize the revenue of the charging service.Simultaneous charger placement and power scheduling problem according to users’ historical tempo-spatial distribution information is fomulated.The formulated problem is a mixed integer linear programming(MILP)problem and is solved by the branch and bound(B&B)algorithm.Extensive simulations in both small-scale and large-scale networks,as well as simulations based on the real data set are conducted to validate the effectiveness of the B&B algorithm.The results show that,the B&B algorithm outperforms greedy algorithm,an algorithm that optimizes charger placement and power scheduling separately,in most of the simulation scenarios,and reaches the optimum in small-scale instances.