Scholarlink

The integration of Space-air-ground power internet of things (SAGPloT) and multi-tier computing has become a key technology to deal with frequent extreme weather disasters and ensure the safe and stable operation of power communication systems. However, the design of SAG-PIoT involves more strict low energy consumption requirements than the traditional SAG networks. In this work, we consider a nonorthogonal multiple access (NOMA) and multi-tier computing assisted SAG-PloT, and investigate the weighted energy minimization problem from the energy-efficiency perspective. Moreover, we decouple the problem into two subproblems and propose a joint optimal power control, computation resource allocation and unmanned aerial vehicle (UAV) trajectory (JOPCT) algorithm. Numerical results show that the proposed algorithm in this work can significantly reduce system energy consumption and efficiently plan UAV trajectories to serve more PIoT devices than the benchmark algorithms. The provided results can offer useful information for design of future space-air-ground power internet of things networks.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Optimization of Energy Consumption with Resource Allocation and UAV Trajectory in Space-Air-Ground Power Internet of Things

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Boxuan Liu,
  • Yuanyuan Gao,
  • Xinru Wang,
  • Xiaobo Liu,
  • Suiyan Geng,
  • Jiakai Hao,
  • Zhiyu Chen,
  • Hongxi Zhou

摘要

The integration of Space-air-ground power internet of things (SAGPloT) and multi-tier computing has become a key technology to deal with frequent extreme weather disasters and ensure the safe and stable operation of power communication systems. However, the design of SAG-PIoT involves more strict low energy consumption requirements than the traditional SAG networks. In this work, we consider a nonorthogonal multiple access (NOMA) and multi-tier computing assisted SAG-PloT, and investigate the weighted energy minimization problem from the energy-efficiency perspective. Moreover, we decouple the problem into two subproblems and propose a joint optimal power control, computation resource allocation and unmanned aerial vehicle (UAV) trajectory (JOPCT) algorithm. Numerical results show that the proposed algorithm in this work can significantly reduce system energy consumption and efficiently plan UAV trajectories to serve more PIoT devices than the benchmark algorithms. The provided results can offer useful information for design of future space-air-ground power internet of things networks.