UAV-Enabled Uplink Non-Orthogonal Multiple Access System: Joint Deployment and Power Control

In order to overcome the inherent latency in multi-user orthogonal multiple access (OMA) unmanned aerial vehicle (UAV) networks. In this paper, we investigate a UAV-enabled uplink non-orthogonal multiple access (NOMA) network, where a UAV is deployed to collect the messages transmitted by the ground...

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Published in:	IEEE transactions on vehicular technology Vol. 69; no. 9; pp. 10090 - 10102
Main Authors:	Lu, Jinhui, Wang, Yuntian, Liu, Tingting, Zhuang, Zhihong, Zhou, Xiaobo, Shu, Feng, Han, Zhu
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.09.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Complexity Computational geometry Convex analysis Convexity Iterative algorithms Iterative methods Mixed integer Network latency NOMA Nonorthogonal multiple access Optimization Penalty function Power control Silicon carbide Trajectory UAV deployment UAV networks Unmanned aerial vehicles Uplink uplink NOMA
ISSN:	0018-9545, 1939-9359
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Abstract	In order to overcome the inherent latency in multi-user orthogonal multiple access (OMA) unmanned aerial vehicle (UAV) networks. In this paper, we investigate a UAV-enabled uplink non-orthogonal multiple access (NOMA) network, where a UAV is deployed to collect the messages transmitted by the ground users. To maximize the users' sum-rate, we formulate a optimization problem, in which the UAV deployment position and the power control are jointly optimized subject to the transmission power constraints and the quality of service (QoS) constraints. However, this problem is a mixed integer non-convex optimization problem and thus it is difficult to solve directly. Therefore, we first transform the non-convex optimization problem into a convex one based on the first-order approximation technique and the penalty function method. Then, a successive convex approximate (SCA) technique based iterative algorithm as well as its initialization scheme are developed to find a suboptimal solution to the original problem. Afterwards, a low-complexity approximate algorithm is proposed to reduce the high computational complexity of the iterative algorithm. Numerical results show that our proposed iterative algorithm and low-complexity approximate algorithm can achieve a similar performance, and they can efficiently improve the sum-rate compared with OMA scheme and conventional NOMA scheme.
AbstractList	In order to overcome the inherent latency in multi-user orthogonal multiple access (OMA) unmanned aerial vehicle (UAV) networks. In this paper, we investigate a UAV-enabled uplink non-orthogonal multiple access (NOMA) network, where a UAV is deployed to collect the messages transmitted by the ground users. To maximize the users' sum-rate, we formulate a optimization problem, in which the UAV deployment position and the power control are jointly optimized subject to the transmission power constraints and the quality of service (QoS) constraints. However, this problem is a mixed integer non-convex optimization problem and thus it is difficult to solve directly. Therefore, we first transform the non-convex optimization problem into a convex one based on the first-order approximation technique and the penalty function method. Then, a successive convex approximate (SCA) technique based iterative algorithm as well as its initialization scheme are developed to find a suboptimal solution to the original problem. Afterwards, a low-complexity approximate algorithm is proposed to reduce the high computational complexity of the iterative algorithm. Numerical results show that our proposed iterative algorithm and low-complexity approximate algorithm can achieve a similar performance, and they can efficiently improve the sum-rate compared with OMA scheme and conventional NOMA scheme.
Author	Shu, Feng Zhou, Xiaobo Liu, Tingting Lu, Jinhui Wang, Yuntian Han, Zhu Zhuang, Zhihong
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Snippet	In order to overcome the inherent latency in multi-user orthogonal multiple access (OMA) unmanned aerial vehicle (UAV) networks. In this paper, we investigate...
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SubjectTerms	Algorithms Complexity Computational geometry Convex analysis Convexity Iterative algorithms Iterative methods Mixed integer Network latency NOMA Nonorthogonal multiple access Optimization Penalty function Power control Silicon carbide Trajectory UAV deployment UAV networks Unmanned aerial vehicles Uplink uplink NOMA
Title	UAV-Enabled Uplink Non-Orthogonal Multiple Access System: Joint Deployment and Power Control
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