Multiple Access in the Era of Distributed Computing and Edge Intelligence

This article 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 multiaccess 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 (FL), federated distillation (FD), split learning (SL), reinforcement learning (RL), 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.

I. Introduction

The next generation of wireless communication networks is expected to provide intelligence, limitless connectivity, and full synchronization of the physical and digital worlds, paving the way for the development of novel applications both indoors and outdoors. Specifically, the key performance indicator (KPI) expectations of academia and industry are converging toward an ever-increasing deployment of machine-type nodes in 2-D/3-D service areas (10 Gb/s/m3), and the need for even higher reliability ( frame error rate), lower latency (0.1 ms), higher data rates (1 Tb/s), and higher energy efficiency (1 pJ/bit) [1], [2], [3].