Aiming at the problem of limited energy stored in unmanned aerial vehicle (UAV), a resource allocation strategy for UAV-assisted edge computing in wireless powered communication networks is investigated in this paper. By deploying a laser beam director on the ground, sufficient energy can be provided for the UAV in a short period of time. Then, multiple ground terminals obtain energy from this UAV by radio frequency energy harvesting method and offload their computational tasks to the UAV with edge server. The resource allocation problem is modeled as an optimization problem. The optimization objective is to minimize the total energy consumption of the UAV subject to the constraints of energy and data causality, computational resources, and transmitting power. The suboptimal solution is obtained by introducing an imperialist competitive algorithm. Simulation results show that the imperialist competitive algorithm consumes less energy compared with the particle swarm optimization algorithm and the equal upload time allocation method.
研究了二部许可图下的两台平行机排序问题,针对加工时间仅取 2,3 且目标函数为最小化最大完工时间这一特殊情形,设计了基于匹配方法的近似算法,证明了算法的最坏情况界为 5/4.
采用 0.25 μm GaAs pHEMT工艺设计了一款 L波段无源高线性度混频器.混频器由片上无源巴伦、本振驱动放大器及无源双平衡混频器核心组成,芯片尺寸为 3.1 mm×2.1 mm×0.1 mm.测试结果表明,本振输入频率为 800～1 000 MHz,射频输入频率为 960～1 080 MHz 时,相应的中频输出频率为 0.1～250.0 MHz,变频损耗为 9.5 dB,输入 1dB压缩点为 19 dBm,功耗为 0.24 W,单边带噪声系数小于 11 dB,3 个端口之间的隔离度都在 33 dBc以上.
