TY - JOUR
T1 - UAV-RIS Assisted Multiuser Communications Through Transmission Strategy Optimization
T2 - GBD Application
AU - Huroon, Aamer Mohamed
AU - Huang, Yu Chih
AU - Wang, Li Chun
N1 - Publisher Copyright:
© 2024 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
PY - 2024/6/1
Y1 - 2024/6/1
N2 - In this article, we present a transmission strategy optimization technique for multiple unmanned aerial vehicles (UAVs) base stations assisted by a terrestrial reconfigurable intelligent surface (RIS). While each UAV is designed to serve a particular group of users, whether a UAV is assisted by RIS depends on the distance between the UAV and the terrestrial RIS. As such, a joint optimization problem of the allocation of RIS clusters for each associated UAV and the computation of phase rotations corresponding to terrestrial RIS elements is formulated. Based on the generalized Benders decomposition (GBD), we develop an algorithm to solve the problem efficiently for this mixed integer non-linear programming problem (MINLP) in two cases: 1) treating interference as noise (TIN) and 2) applying successive interference cancellation (SIC) at user terminals. Through extensive simulations, we provide evidence of our algorithm’s superiority over existing methods, including alternating optimization and multi-task learning. By checking the upper and lower bounds provided by the proposed algorithm, we show that our algorithm attains the global optimality for the considered simulations. Notably, our results also reaffirm the common belief that SIC decoding can provide performance enhancement over TIN decoding in the UAV-RIS-assisted systems.
AB - In this article, we present a transmission strategy optimization technique for multiple unmanned aerial vehicles (UAVs) base stations assisted by a terrestrial reconfigurable intelligent surface (RIS). While each UAV is designed to serve a particular group of users, whether a UAV is assisted by RIS depends on the distance between the UAV and the terrestrial RIS. As such, a joint optimization problem of the allocation of RIS clusters for each associated UAV and the computation of phase rotations corresponding to terrestrial RIS elements is formulated. Based on the generalized Benders decomposition (GBD), we develop an algorithm to solve the problem efficiently for this mixed integer non-linear programming problem (MINLP) in two cases: 1) treating interference as noise (TIN) and 2) applying successive interference cancellation (SIC) at user terminals. Through extensive simulations, we provide evidence of our algorithm’s superiority over existing methods, including alternating optimization and multi-task learning. By checking the upper and lower bounds provided by the proposed algorithm, we show that our algorithm attains the global optimality for the considered simulations. Notably, our results also reaffirm the common belief that SIC decoding can provide performance enhancement over TIN decoding in the UAV-RIS-assisted systems.
KW - Aerial-terrestrial communications
KW - generalized Benders decomposition
KW - mixed-integer nonlinear programming
KW - reconfigurable intelligent surfaces
KW - transmission strategy
UR - http://www.scopus.com/inward/record.url?scp=85184817376&partnerID=8YFLogxK
U2 - 10.1109/TVT.2024.3362066
DO - 10.1109/TVT.2024.3362066
M3 - Article
AN - SCOPUS:85184817376
SN - 0018-9545
VL - 73
SP - 8584
EP - 8597
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 6
ER -