Energy Harvesting and Resource Allocation for Cache-Enabled UAV Based IoT NOMA Networks

Huifang Li, Jing Li, Meng Liu, Zhiguo Ding, Fengkui Gong

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


This paper investigates a novel joint content caching and energy harvesting scheme to enhance unmanned aerial vehicle (UAV) communications in Internet of Things non-orthogonal multiple access (NOMA) network, where a UAV is acted as an aerial relay to serve users on demand. In particular, a neoteric gravitational search-based multi-constraint optimization algorithm is designed to maximize the throughput of the served users by jointly optimizing power allocation, energy harvesting, and time scheduling schemes. The algorithm engages two main characteristics: 1) classification of multiple constraints, which is for reducing the complexity of the problem solving process due to multiple iterations, and 2) design of force sets, which aims to enhance the global search for the optimal solution at the feasible region boundary. Finally, simulations are provided to show the effective convergence and superiority of the proposed algorithm.

Original languageBritish English
Pages (from-to)9625-9630
Number of pages6
JournalIEEE Transactions on Vehicular Technology
Issue number9
StatePublished - Sep 2021


  • gravitational search
  • NOMA
  • resource allocation
  • Simultaneous wireless information and power transfer
  • UAV


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