TY - JOUR
T1 - Developing NOMA to Next Generation Multiple Access
T2 - Future Vision and Research Opportunities
AU - Liu, Yuanwei
AU - Yi, Wenqiang
AU - Ding, Zhiguo
AU - Liu, Xiao
AU - Dobre, Octavia A.
AU - Al-Dhahir, Naofal
N1 - Publisher Copyright:
© 2002-2012 IEEE.
PY - 2022/12/1
Y1 - 2022/12/1
N2 - As a prominent member of the Next Generation Multiple Access (NGMA) family, Non-Orthogonal Multiple Access (NOMA) has been recognized as a promising multiple access candidate for the Sixth-Generation (6G) networks. This article focuses on applying NOMA in 6G networks, with an emphasis on proposing the so-called One Basic Principle Plus Four New concept. Successive Interference Cancellation (SIC) importance becomes evident, starting with the basic NOMA principle. In particular, this article discusses the advantages and drawbacks of channel-state-information-based SIC and quality-of-service-based-SIC. In addition, it explores applying NOMA to meet the new 6G performance requirements, especially for massive connectivity. Further, this article considers integrating NOMA with new physical layer techniques, followed by introducing new application scenarios for NOMA toward 6G. Finally, the article investigates applying machine learning in NOMA networks, ushering in the machine learning empowered NGMA era.
AB - As a prominent member of the Next Generation Multiple Access (NGMA) family, Non-Orthogonal Multiple Access (NOMA) has been recognized as a promising multiple access candidate for the Sixth-Generation (6G) networks. This article focuses on applying NOMA in 6G networks, with an emphasis on proposing the so-called One Basic Principle Plus Four New concept. Successive Interference Cancellation (SIC) importance becomes evident, starting with the basic NOMA principle. In particular, this article discusses the advantages and drawbacks of channel-state-information-based SIC and quality-of-service-based-SIC. In addition, it explores applying NOMA to meet the new 6G performance requirements, especially for massive connectivity. Further, this article considers integrating NOMA with new physical layer techniques, followed by introducing new application scenarios for NOMA toward 6G. Finally, the article investigates applying machine learning in NOMA networks, ushering in the machine learning empowered NGMA era.
UR - http://www.scopus.com/inward/record.url?scp=85133757273&partnerID=8YFLogxK
U2 - 10.1109/MWC.007.2100553
DO - 10.1109/MWC.007.2100553
M3 - Article
AN - SCOPUS:85133757273
SN - 1536-1284
VL - 29
SP - 120
EP - 127
JO - IEEE Wireless Communications
JF - IEEE Wireless Communications
IS - 6
ER -