Energy-efficient resource allocation for dual-NOMA-UAV assisted Internet of Things

Zechen Liu, Xin Liu, Victor C. M. Leung, Tariq S Durrani

Research output: Contribution to journalArticlepeer-review

Abstract

Employing unmanned aerial vehicles (UAVs) characterized by low cost, high maneuverability, and on-demand deployment as aerial base stations (BSs) of Internet of Things (IoT) can guarantee communication performance in the absence of terrestrial BSs. However, the limited energy budget of UAV constrains its development. In this paper, a dual-UAV-assisted IoT using non-orthogonal multiple access (NOMA) is proposed to improve IoT capacity. To reduce energy consumption of the UAVs while ensuring a certain throughput, a joint resource optimization problem of communication scheduling, transmit power and motion parameters of UAVs is formulated to maximize energy efficiency of UAVs. To solve the proposed non-convex optimization problem, we present an alternating iterative optimization algorithm to alternately optimize three sub-problems: communication scheduling optimization, UAV transmit power optimization and UAV motion parameters optimization, each of which can be converted into convex optimization and solved using Lagrange multiplier method, subgradient descent method and successive convex approximation (SCA). The numerical results show that optimizing UAV motion parameters can effectively improve energy efficiency of UAVs, and the proposed dual-NOMA-UAV assisted IoT can achieve higher energy efficiency than the orthogonal multiple access (OMA)-UAV assisted IoT.
Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalIEEE Transactions on Vehicular Technology
Early online date3 Nov 2022
DOIs
Publication statusE-pub ahead of print - 3 Nov 2022

Keywords

  • IoT
  • UAV
  • NOMA
  • resource allocation
  • energy efficiency maximization
  • Internet of Things
  • unmanned aerial vehicles (UAVs)

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