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 in | IEEE transactions on vehicular technology Vol. 70; no. 7; pp. 6898 - 6912 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.07.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
ISSN | 0018-9545 1939-9359 |
DOI | 10.1109/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. |
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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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