  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. Starting with the basic
NOMA principle, the importance of successive interference cancellation (SIC)
becomes evident. In particular, the advantages and drawbacks of both the
channel state information based SIC and quality-of-service based SIC are
discussed. Then, the application of NOMA to meet the new 6G performance
requirements, especially for massive connectivity, is explored. Furthermore,
the integration of NOMA with new physical layer techniques is considered,
followed by introducing new application scenarios for NOMA towards 6G. Finally,
the application of machine learning in NOMA networks is investigated, ushering
in the machine learning empowered NGMA era.
