Please use this identifier to cite or link to this item:
Title: Reconfigurable intelligent surface-assisted aerial-terrestrial communications via multi-task learning
Authors: Cao, Xuelin
Yang, Bo
Huang, Chongwen
Yuen, Chau
Renzo, Marco Di
Niyato, Dusit
Han, Zhu
Keywords: Engineering::Computer science and engineering
Issue Date: 2021
Source: Cao, X., Yang, B., Huang, C., Yuen, C., Renzo, M. D., Niyato, D. & Han, Z. (2021). Reconfigurable intelligent surface-assisted aerial-terrestrial communications via multi-task learning. IEEE Journal On Selected Areas in Communications, 39(10), 3035-3050.
Journal: IEEE Journal on Selected Areas in Communications
Abstract: The aerial-terrestrial communication system constitutes an efficient paradigm for supporting and complementing terrestrial communications. However, the benefits of such a system cannot be fully exploited, especially when the line-of-sight (LoS) transmissions are prone to severe deterioration due to complex propagation environments in urban areas. The emerging technology of reconfigurable intelligent surfaces (RISs) has recently become a potential solution to mitigate propagation-induced impairments and improve wireless network coverage. Motivated by these considerations, in this paper, we address the coverage and link performance problems of the aerial-terrestrial communication system by proposing an RIS-assisted transmission strategy. In particular, we design an adaptive RIS-assisted transmission protocol, in which the channel estimation, transmission strategy, and data transmission are independently implemented in a frame. On this basis, we formulate an RIS-assisted transmission strategy optimization problem as a mixed-integer non-linear program (MINLP) to maximize the overall system throughput. We then employ multi-task learning to speed up the solution to the problem. Benefiting from multi-task learning, the computation time is reduced by about four orders of magnitude. Numerical results show that the proposed RIS-assisted transmission protocol significantly improves the system throughput and reduces the transmit power.
ISSN: 0733-8716
DOI: 10.1109/JSAC.2021.3088634
Schools: School of Computer Science and Engineering 
Rights: © 2021 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

Citations 10

Updated on Sep 16, 2023

Web of ScienceTM
Citations 10

Updated on Sep 11, 2023

Page view(s)

Updated on Sep 22, 2023

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.