| 摘要: |
| 针对大规模物联网场景下无人机通信感知一体化系统存在的重复感知和能量受限等问题，提出了一种基于聚类算法的能效优化方案。该方案在满足无人机的移动性和感知能力约束下，通过联合设计无人机的三维轨迹和发射功率来最大化系统能效。由于该问题是非凸的，首先将其解耦为两个子问题，然后利用模拟退火算法和标准凸优化技术来求解无人机的悬停位置和飞行速度以获取最优轨迹，最后根据最优轨迹推导发射功率的闭合表达式，求得每个悬停位置的最优发射功率。与传统的二维和三维方案相比，所提基于聚类的能效优化方案在收敛速度提高4倍的基础上能提升20%~30%系统能效。 |
| 关键词: 大规模物联网 无人机通信感知一体化 能效优化 无人机轨迹设计 功率分配 |
| DOI：10.20079/j.issn.1001-893x.230825001 |
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| 基金项目:江苏省重点研发计划项目（BE2021013-1）；江苏省未来网络科研项目（FNSRFP-2021-YB-42） |
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| Energy Efficiency Optimization for UAV-enabled Integrated Sensing and Communication in Massive IoT Scenario |
| SONG Lizhi,JI Zengshuan,ZENG Feng,WANG Wei,YANG Yongjie |
| (1.School of Information Science and Technology,Nantong University,Nantong 226019,China;2.Nantong Research Institute for Advanced Communication Technologies,Nantong 226019,China) |
| Abstract: |
| Taking into account the repetition sensing and energy limitation of UAV-enabled integrated sensing and communication in massive Internet of Things(IoT) scenarios,the authors propose a novel energy-efficient optimization scheme based on clustering algorithm.The scheme aims to maximize the energy efficiency of the UAV by jointly optimizing the UAV three-dimensional(3D) trajectory and transmit power while meeting the constraints of the mobility and sensing ability of the UAV.To deal with this non-convex optimization problem,the original problem is decomposed into two subproblems.Then,the simulated annealing algorithms and convex optimization techniques are adopted to optimize the hovering positions and flight speeds,so as to abtain the optimal trajectory of the UAV.Finally,according to the optimal trajectory,the closed-form expressions for the transmission power are derived.The proposed clustering-based energy-efficient optimization algorithm can obtain 4 times convergence speed and 20%~30% energy efficient improvement compared with the traditional two-dimensional(2D) and 3D methods. |
| Key words: massive IoT UAV-enabled integrated sensing and communication energy efficiency optimization UAV trajectory design power allocation |
