TY - JOUR
T1 - Intelligent Reflecting Surface Enhanced Multi-UAV NOMA Networks
AU - Mu, Xidong
AU - Liu, Yuanwei
AU - Guo, Li
AU - Lin, Jiaru
AU - Poor, H. Vincent
N1 - Funding Information:
Manuscript received October 22, 2020; revised February 5, 2021; accepted April 12, 2021. Date of publication June 14, 2021; date of current version September 16, 2021. This work was supported in part by the Beijing Natural Science Foundation under Grant L192032, in part by the National Key Research and Development Program of China under Grant 2019YFB1406500, in part by the Key Project Plan of Blockchain in Ministry of Education of the People’s Republic of China under Grant 2020KJ010802, in part by the Shandong Province Key Research and Development Program, China, under Grant 2019JZZY020901, in part by the National Natural Science Foundation of China under Grant 61771066, and in part by the U.S. National Science Foundation under Grant CCF–1908308. (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: muxidong@bupt.edu.cn; guoli@bupt.edu.cn; jrlin@bupt.edu.cn).
Publisher Copyright:
© 1983-2012 IEEE.
PY - 2021/10
Y1 - 2021/10
N2 - Intelligent reflecting surface (IRS) enhanced multi-unmanned aerial vehicle (UAV) non-orthogonal multiple access (NOMA) networks are investigated. A new transmission framework is proposed, where multiple UAV-mounted base stations employ NOMA to serve multiple groups of ground users with the aid of an IRS. The three-dimensional (3D) placement and transmit power of UAVs, the reflection matrix of the IRS, and the NOMA decoding orders among users are jointly optimized for maximization of the sum rate of considered networks. To tackle the formulated mixed-integer non-convex optimization problem with coupled variables, a block coordinate descent (BCD)-based iterative algorithm is developed. Specifically, the original problem is decomposed into three subproblems, which are alternately solved by exploiting the penalty-based method and the successive convex approximation technique. The proposed BCD-based algorithm is demonstrated to be able to obtain a stationary point of the original problem with polynomial time complexity. Numerical results show that: 1) the proposed NOMA-IRS scheme for multi-UAV networks achieves a higher sum rate compared to the benchmark schemes, i.e., orthogonal multiple access (OMA)-IRS and NOMA without IRS; 2) the use of IRS is capable of providing performance gain for multi-UAV networks by both enhancing channel qualities of UAVs to their served users and mitigating the inter-UAV interference; and 3) optimizing the UAV placement can make the sum rate gain brought by NOMA more distinct due to the flexible decoding order design.
AB - Intelligent reflecting surface (IRS) enhanced multi-unmanned aerial vehicle (UAV) non-orthogonal multiple access (NOMA) networks are investigated. A new transmission framework is proposed, where multiple UAV-mounted base stations employ NOMA to serve multiple groups of ground users with the aid of an IRS. The three-dimensional (3D) placement and transmit power of UAVs, the reflection matrix of the IRS, and the NOMA decoding orders among users are jointly optimized for maximization of the sum rate of considered networks. To tackle the formulated mixed-integer non-convex optimization problem with coupled variables, a block coordinate descent (BCD)-based iterative algorithm is developed. Specifically, the original problem is decomposed into three subproblems, which are alternately solved by exploiting the penalty-based method and the successive convex approximation technique. The proposed BCD-based algorithm is demonstrated to be able to obtain a stationary point of the original problem with polynomial time complexity. Numerical results show that: 1) the proposed NOMA-IRS scheme for multi-UAV networks achieves a higher sum rate compared to the benchmark schemes, i.e., orthogonal multiple access (OMA)-IRS and NOMA without IRS; 2) the use of IRS is capable of providing performance gain for multi-UAV networks by both enhancing channel qualities of UAVs to their served users and mitigating the inter-UAV interference; and 3) optimizing the UAV placement can make the sum rate gain brought by NOMA more distinct due to the flexible decoding order design.
KW - Intelligent reflecting surfaces
KW - non-orthogonal multiple access
KW - placement optimization
KW - unmanned aerial vehicles
UR - http://www.scopus.com/inward/record.url?scp=85112232862&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85112232862&partnerID=8YFLogxK
U2 - 10.1109/JSAC.2021.3088679
DO - 10.1109/JSAC.2021.3088679
M3 - Article
AN - SCOPUS:85112232862
SN - 0733-8716
VL - 39
SP - 3051
EP - 3066
JO - IEEE Journal on Selected Areas in Communications
JF - IEEE Journal on Selected Areas in Communications
IS - 10
ER -