Multiple Access in the Era of Distributed Computing and Edge
  Intelligence
Nikos G. Evgenidis Nikos A. Mitsiou Vasiliki I. Koutsioumpa Sotiris A. Tegos Panagiotis D. Diamantoulakis George K. Karagiannidis
This paper focuses on the latest research and innovations in fundamental
next-generation multiple access (NGMA) techniques and the coexistence with
other key technologies for the sixth generation (6G) of wireless networks. In
more detail, we first examine multi-access edge computing (MEC), which is
critical to meeting the growing demand for data processing and computational
capacity at the edge of the network, as well as network slicing. We then
explore over-the-air (OTA) computing, which is considered to be an approach
that provides fast and efficient computation of various functions. We also
explore semantic communications, identified as an effective way to improve
communication systems by focusing on the exchange of meaningful information,
thus minimizing unnecessary data and increasing efficiency. The
interrelationship between machine learning (ML) and multiple access
technologies is also reviewed, with an emphasis on federated learning,
federated distillation, split learning, reinforcement learning, and the
development of ML-based multiple access protocols. Finally, the concept of
digital twinning and its role in network management is discussed, highlighting
how virtual replication of physical networks can lead to improvements in
network efficiency and reliability.