TY - JOUR
T1 - Energy Harvesting and Resource Allocation for Cache-Enabled UAV Based IoT NOMA Networks
AU - Li, Huifang
AU - Li, Jing
AU - Liu, Meng
AU - Ding, Zhiguo
AU - Gong, Fengkui
N1 - Funding Information:
Thisworkwas supported by the Key RandD Program of Shaanxi Province under Grant 2019ZDLGY07-05.
Funding Information:
Manuscript received January 22, 2021; revised June 2, 2021 and July 15, 2021; accepted July 16, 2021. Date of publication July 21, 2021; date of current version September 17, 2021. This work was supported by the Key R&D Program of Shaanxi Province under Grant 2019ZDLGY07-05. The review of this article was coordinated by Prof. Ying-Dar Lin. (Corresponding author: Jing Li.) Huifang Li, Jing Li, and Fengkui Gong are with the State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an 710071, China (e-mail: [email protected]; [email protected]; [email protected]).
Publisher Copyright:
© 1967-2012 IEEE.
PY - 2021/9
Y1 - 2021/9
N2 - This paper investigates a novel joint content caching and energy harvesting scheme to enhance unmanned aerial vehicle (UAV) communications in Internet of Things non-orthogonal multiple access (NOMA) network, where a UAV is acted as an aerial relay to serve users on demand. In particular, a neoteric gravitational search-based multi-constraint optimization algorithm is designed to maximize the throughput of the served users by jointly optimizing power allocation, energy harvesting, and time scheduling schemes. The algorithm engages two main characteristics: 1) classification of multiple constraints, which is for reducing the complexity of the problem solving process due to multiple iterations, and 2) design of force sets, which aims to enhance the global search for the optimal solution at the feasible region boundary. Finally, simulations are provided to show the effective convergence and superiority of the proposed algorithm.
AB - This paper investigates a novel joint content caching and energy harvesting scheme to enhance unmanned aerial vehicle (UAV) communications in Internet of Things non-orthogonal multiple access (NOMA) network, where a UAV is acted as an aerial relay to serve users on demand. In particular, a neoteric gravitational search-based multi-constraint optimization algorithm is designed to maximize the throughput of the served users by jointly optimizing power allocation, energy harvesting, and time scheduling schemes. The algorithm engages two main characteristics: 1) classification of multiple constraints, which is for reducing the complexity of the problem solving process due to multiple iterations, and 2) design of force sets, which aims to enhance the global search for the optimal solution at the feasible region boundary. Finally, simulations are provided to show the effective convergence and superiority of the proposed algorithm.
KW - gravitational search
KW - NOMA
KW - resource allocation
KW - Simultaneous wireless information and power transfer
KW - UAV
UR - http://www.scopus.com/inward/record.url?scp=85111009922&partnerID=8YFLogxK
U2 - 10.1109/TVT.2021.3098351
DO - 10.1109/TVT.2021.3098351
M3 - Article
AN - SCOPUS:85111009922
SN - 0018-9545
VL - 70
SP - 9625
EP - 9630
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 9
ER -