TY - JOUR
T1 - Energy-Constrained UAV Data Collection Systems
T2 - NOMA and OMA
AU - Mu, Xidong
AU - Liu, Yuanwei
AU - Guo, Li
AU - Lin, Jiaru
AU - Ding, Zhiguo
N1 - Funding Information:
Manuscript received December 31, 2020; revised April 3, 2021; accepted May 28, 2021. Date of publication June 4, 2021; date of current version July 20, 2021. This work was supported by Beijing Natural Science Foundation under Grant L192032, by the National Key Research and Development Program of China under Grant 2019YFB1406500, by the Key Project Plan of Blockchain in Ministry of Education of the People’s Republic of China under Grant 2020KJ010802, by Shandong Province Key Research and Development Program, China under Grant 2019JZZY020901, and by the National Natural Science Foundation of China under Grant 61771066. The work of Xidong Mu was supported by China Scholarship Council. The review of this article was coordinated by Dr. Joongheon Kim. (Corresponding author: Li Guo.) Xidong Mu, Li Guo, and Jiaru Lin are with the Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China, and also with the School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China (e-mail: [email protected]; [email protected]; [email protected]).
Publisher Copyright:
© 1967-2012 IEEE.
PY - 2021/7
Y1 - 2021/7
N2 - 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.
AB - 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.
KW - Energy-constrained
KW - non-orthogonal multiple access
KW - trajectory design
KW - unmanned aerial vehicle
UR - http://www.scopus.com/inward/record.url?scp=85107331790&partnerID=8YFLogxK
U2 - 10.1109/TVT.2021.3086556
DO - 10.1109/TVT.2021.3086556
M3 - Article
AN - SCOPUS:85107331790
SN - 0018-9545
VL - 70
SP - 6898
EP - 6912
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 7
M1 - 9447204
ER -