针对射频能量捕获传感网(RF Energy Harvesting Wireless Sensor Network,RFEH-WSN)中移动能量源(Energy Transmitter,ET)的充电效率问题,已有的工作主要假设移动ET的充电辐射范围为圆形,而在实际应用中移动ET的充电辐射范围通常被设定为一定角度的扇形。面向有向移动ET的应用场景,该文以最小充电时间和最大覆盖率为目标建立多目标优化模型,利用粒子群算法求解出最优Pareto解集。仿真实验结果表明,该文提出的多目标优化算法可以有效的提高移动ET的充电效率且更适用于非线性模型。

For the charging efficiency of mobile energy transmitter(ET) in RF energy harvesting wireless sensor network(RFEH-WSN),the existing work mainly assumes that the charging radiation range of mobile ET is circular, and the charging radiation range of mobile ET is usually set as a sector at a certain angle in practical applications. Aiming at the application scenario of directed mobile ET, this paper proposed a new multiple object model,and the optimization aims of the model are to minimize the charging time and to maximize the coverage, and uses Particle Swarm Optimization? to solve the optimal Pareto solution set. The results of simulation experiments show that the multi-objective optimization algorithm proposed in this paper can effectively improve the charging efficiency of mobile ET and is more suitable for nonlinear model.

国家自然科学基金(62271341)；山西省科技创新人才团队(202204051001018)