TY - JOUR
T1 - Reconfigurable intelligent surface (RIS)-assisted non-terrestrial network (NTN) based 6G communications: A contemporary survey
AU - Worka, Chika E.
AU - Khan, Faheem A.
AU - Ahmed, Qasim Zeeshan
AU - Sureephong, Pradorn
AU - Alade, Temitope
N1 - Funding Information: Part of this work is supported by the European Union through the Horizon Europe Research and Innovation Programme under the Marie Sklodowska-Curie grant agreement No. 101086218.
PY - 2024/11/1
Y1 - 2024/11/1
N2 - This article examines the transformative potential of integrating reconfigurable intelligent surfaces (RISs) into sixth-generation (6G) wireless non-terrestrial networks (NTNs). The focus is on the RIS’s capability to address diverse user requirements, including secure data transmission, power efficiency, extended coverage, and enhanced data rates. The paper delves into the synergy between RISs and NTNs, emphasizing key components like multiple-input multiple-output (MIMO) systems and advanced radio communications. Additionally, it highlights the crucial role of artificial intelligence (AI) and machine learning (ML) in optimizing RIS-based beamforming to solve scientific and engineering challenges while ensuring energy efficiency and sustainability in NTN operations. By positioning RISs as a key enabler in shaping the future of wireless communication systems, this research underscores their significance in unlocking the full potential of NTNs and advancing next-generation wireless communications. This paper contributes valuable insights and projections for future research directions, highlighting RISs’ potential to revolutionize NTNs for 6G technologies.
AB - This article examines the transformative potential of integrating reconfigurable intelligent surfaces (RISs) into sixth-generation (6G) wireless non-terrestrial networks (NTNs). The focus is on the RIS’s capability to address diverse user requirements, including secure data transmission, power efficiency, extended coverage, and enhanced data rates. The paper delves into the synergy between RISs and NTNs, emphasizing key components like multiple-input multiple-output (MIMO) systems and advanced radio communications. Additionally, it highlights the crucial role of artificial intelligence (AI) and machine learning (ML) in optimizing RIS-based beamforming to solve scientific and engineering challenges while ensuring energy efficiency and sustainability in NTN operations. By positioning RISs as a key enabler in shaping the future of wireless communication systems, this research underscores their significance in unlocking the full potential of NTNs and advancing next-generation wireless communications. This paper contributes valuable insights and projections for future research directions, highlighting RISs’ potential to revolutionize NTNs for 6G technologies.
KW - 6G communications
KW - artificial intelligence
KW - beamforming optimization
KW - energy efficiency
KW - high-altitude non-terrestrial platforms
KW - machine learning
KW - non-terrestrial networks
KW - reconfigurable intelligent surfaces
UR - http://www.scopus.com/inward/record.url?scp=85208582457&partnerID=8YFLogxK
U2 - 10.3390/s24216958
DO - 10.3390/s24216958
M3 - Article
VL - 24
JO - Sensors
JF - Sensors
SN - 1424-8220
IS - 21
M1 - 6958
ER -