TY - JOUR
T1 - Artificial Intelligence for Wireless Physical-Layer Technologies (AI4PHY)
T2 - A Comprehensive Survey
AU - Ye, Neng
AU - Miao, Sirui
AU - Pan, Jianxiong
AU - Ouyang, Qiaolin
AU - Li, Xiangming
AU - Hou, Xiaolin
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2024/6/1
Y1 - 2024/6/1
N2 - Artificial intelligence (AI) has become a promising solution for meeting the stringent performance requirements on wireless physical layer in sixth-generation (6G) communication systems, due to its strong ability to learn complex model, achieve end-to-end optimization and adapt to dynamic environments. This article provides a comprehensive review with respect to artificial intelligence for wireless physical-layer technologies (AI4PHY). Specifically, we first analyze the characteristics of the classic AI techniques and their potential applications for physical-layer technologies. Then we study the AI-enhanced designs from the point of view of the basic physical-layer modules, including coding, modulation, multiple access, multiple-input-multiple-output (MIMO), channel estimation, as well as relay transmission. The standardization progress of AI4PHY in 3GPP is also discussed. Based on the current AI4PHY researches, we propose some potential future research directions to inspire and encourage the further exploration.
AB - Artificial intelligence (AI) has become a promising solution for meeting the stringent performance requirements on wireless physical layer in sixth-generation (6G) communication systems, due to its strong ability to learn complex model, achieve end-to-end optimization and adapt to dynamic environments. This article provides a comprehensive review with respect to artificial intelligence for wireless physical-layer technologies (AI4PHY). Specifically, we first analyze the characteristics of the classic AI techniques and their potential applications for physical-layer technologies. Then we study the AI-enhanced designs from the point of view of the basic physical-layer modules, including coding, modulation, multiple access, multiple-input-multiple-output (MIMO), channel estimation, as well as relay transmission. The standardization progress of AI4PHY in 3GPP is also discussed. Based on the current AI4PHY researches, we propose some potential future research directions to inspire and encourage the further exploration.
KW - Artificial intelligence
KW - MIMO systems
KW - communication systems
KW - encoding
KW - modulation
KW - standardization
UR - http://www.scopus.com/inward/record.url?scp=85189136943&partnerID=8YFLogxK
U2 - 10.1109/TCCN.2024.3382973
DO - 10.1109/TCCN.2024.3382973
M3 - Article
AN - SCOPUS:85189136943
SN - 2332-7731
VL - 10
SP - 729
EP - 755
JO - IEEE Transactions on Cognitive Communications and Networking
JF - IEEE Transactions on Cognitive Communications and Networking
IS - 3
ER -