Energy-Constrained UAV Data Collection Systems: NOMA and OMA

This paper investigates unmanned aerial vehicle (UAV) data collection systems with different multiple access schemes, where a rotary-wing UAV is dispatched to collect data from multiple ground nodes (GNs). Our goal is to maximize the minimum UAV data collection throughput from GNs for both orthogona...

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Published inIEEE transactions on vehicular technology Vol. 70; no. 7; pp. 6898 - 6912
Main Authors Mu, Xidong, Liu, Yuanwei, Guo, Li, Lin, Jiaru, Ding, Zhiguo
Format Journal Article
LanguageEnglish
Published New York IEEE 01.07.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN0018-9545
1939-9359
DOI10.1109/TVT.2021.3086556

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Abstract This paper investigates unmanned aerial vehicle (UAV) data collection systems with different multiple access schemes, where a rotary-wing UAV is dispatched to collect data from multiple ground nodes (GNs). Our goal is to maximize the minimum UAV data collection throughput from GNs for both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) transmission, subject to the energy budgets at both the UAV and GNs, namely double energy limitations . 1) For OMA, we propose an efficient algorithm by invoking alternating optimization (AO) method, where each subproblem is alternately solved by applying successive convex approximation (SCA) technique. 2) For NOMA, we first handle subproblems with fixed decoding order using SCA technique. Then, we develop a penalty-based algorithm to solve the decoding order design subproblem. Numerical results show that: i) The proposed algorithms are capable of improving the max-min throughput performance compared with other benchmark schemes; and ii) NOMA yields a higher performance gain than OMA when GNs have sufficient energy.
AbstractList This paper investigates unmanned aerial vehicle (UAV) data collection systems with different multiple access schemes, where a rotary-wing UAV is dispatched to collect data from multiple ground nodes (GNs). Our goal is to maximize the minimum UAV data collection throughput from GNs for both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) transmission, subject to the energy budgets at both the UAV and GNs, namely double energy limitations . 1) For OMA, we propose an efficient algorithm by invoking alternating optimization (AO) method, where each subproblem is alternately solved by applying successive convex approximation (SCA) technique. 2) For NOMA, we first handle subproblems with fixed decoding order using SCA technique. Then, we develop a penalty-based algorithm to solve the decoding order design subproblem. Numerical results show that: i) The proposed algorithms are capable of improving the max-min throughput performance compared with other benchmark schemes; and ii) NOMA yields a higher performance gain than OMA when GNs have sufficient energy.
Author Guo, Li
Lin, Jiaru
Mu, Xidong
Liu, Yuanwei
Ding, Zhiguo
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SubjectTerms Algorithms
Communication systems
Data collection
Data models
Energy budget
Energy limitation
Energy-constrained
NOMA
non-orthogonal multiple access
Nonorthogonal multiple access
Optimization
Resource management
Trajectory
trajectory design
unmanned aerial vehicle
Unmanned aerial vehicles
Title Energy-Constrained UAV Data Collection Systems: NOMA and OMA
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