  Multiple access (MA) is a crucial part of any wireless system and refers to
techniques that make use of the resource dimensions to serve multiple
users/devices/machines/services, ideally in the most efficient way. Given the
needs of multi-functional wireless networks for integrated communications,
sensing, localization, computing, coupled with the surge of machine learning /
artificial intelligence (AI) in wireless networks, MA techniques are expected
to experience a paradigm shift in 6G and beyond. In this paper, we provide a
tutorial, survey and outlook of past, emerging and future MA techniques and pay
a particular attention to how wireless network intelligence and
multi-functionality will lead to a re-thinking of those techniques. The paper
starts with an overview of orthogonal, physical layer multicasting, space
domain, power domain, ratesplitting, code domain MAs, and other domains, and
highlight the importance of researching universal multiple access to shrink
instead of grow the knowledge tree of MA schemes by providing a unified
understanding of MA schemes across all resource dimensions. It then jumps into
rethinking MA schemes in the era of wireless network intelligence, covering AI
for MA such as AI-empowered resource allocation, optimization, channel
estimation, receiver designs, user behavior predictions, and MA for AI such as
federated learning/edge intelligence and over the air computation. We then
discuss MA for network multi-functionality and the interplay between MA and
integrated sensing, localization, and communications. We finish with studying
MA for emerging intelligent applications before presenting a roadmap toward 6G
standardization. We also point out numerous directions that are promising for
future research.
