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Energy-efficient design for mmWave-enabled NOMA-UAV networks
by
Zhao, Nan
, Zhang, Xiuyin
, Pang, Xiaowei
, Tang, Jie
, Qian, Yi
in
Antenna gain
/ Clustering
/ Computer Science
/ Energy conversion efficiency
/ Energy efficiency
/ Information Systems and Communication Service
/ Iterative algorithms
/ Millimeter waves
/ Networks
/ Nonorthogonal multiple access
/ Placement
/ Research Paper
/ Unmanned aerial vehicles
2021
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Energy-efficient design for mmWave-enabled NOMA-UAV networks
by
Zhao, Nan
, Zhang, Xiuyin
, Pang, Xiaowei
, Tang, Jie
, Qian, Yi
in
Antenna gain
/ Clustering
/ Computer Science
/ Energy conversion efficiency
/ Energy efficiency
/ Information Systems and Communication Service
/ Iterative algorithms
/ Millimeter waves
/ Networks
/ Nonorthogonal multiple access
/ Placement
/ Research Paper
/ Unmanned aerial vehicles
2021
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Energy-efficient design for mmWave-enabled NOMA-UAV networks
by
Zhao, Nan
, Zhang, Xiuyin
, Pang, Xiaowei
, Tang, Jie
, Qian, Yi
in
Antenna gain
/ Clustering
/ Computer Science
/ Energy conversion efficiency
/ Energy efficiency
/ Information Systems and Communication Service
/ Iterative algorithms
/ Millimeter waves
/ Networks
/ Nonorthogonal multiple access
/ Placement
/ Research Paper
/ Unmanned aerial vehicles
2021
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Energy-efficient design for mmWave-enabled NOMA-UAV networks
Journal Article
Energy-efficient design for mmWave-enabled NOMA-UAV networks
2021
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Overview
Owing to the recent advances of non-orthogonal multiple access (NOMA) and millimeter-wave (mmWave), these two technologies are combined in unmanned aerial vehicle (UAV) networks in this paper. However, energy efficiency has become a significant metric for UAVs owning to their limited energy. Thus, we aim to maximize the energy efficiency for mmWave-enabled NOMA-UAV networks by optimizing the UAV placement, hybrid precoding and power allocation. However, the optimization problem is complicated and intractable, which is decomposed into several sub-problems. First, we solve the UAV placement problem by approximating it into a convex one. Then, the hybrid precoding with user clustering is performed to better reap the multi-antenna gain. Particularly, three schemes are proposed, where the cluster head selection algorithm is adopted while considering different equivalent channels of users. Finally, the power allocation is optimized to maximize the energy efficiency, which is converted to convex and solved via an iterative algorithm. Simulation results are provided to evaluate the performance of the proposed schemes.
Publisher
Science China Press,Springer Nature B.V
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