Multiple Access Techniques for Intelligent and Multifunctional 6G: Tutorial, Survey, and Outlook

Bruno Clerckx, Yijie Mao, Zhaohui Yang, Mingzhe Chen, Ahmed Alkhateeb, Liang Liu, Min Qiu, Jinhong Yuan, Vincent W.S. Wong, Juan Montojo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Multiple access (MA) is a crucial part of any wireless system and refers to techniques that make use of the resource dimensions (e.g., time, frequency, power, antenna, code, and message) to serve multiple users/devices/machines/ services, ideally in the most efficient way. Given the increasing need of multifunctional wireless networks for integrated communications, sensing, localization, and computing, coupled with the surge of machine learning (ML)/artificial intelligence (AI) in wireless networks, MA techniques are expected to experience a paradigm shift in 6G and beyond. In this article, we provide a tutorial, survey, and outlook on past, emerging, and future MA techniques and pay particular attention to how wireless network intelligence and multifunctionality will lead to a rethinking of those techniques. This article starts with an overview of orthogonal, physical-layer multicasting, space domain, power domain (PD), rate-splitting, code-domain MAs, MAs in other domains, and random access (RA), and highlights the importance of conducting research in universal MA (UMA) 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, and receiver designs, for different MA schemes, and MA for AI such as federated learning (FL)/edge intelligence and over-the-air computation (AirComp). We then discuss MA for network multifunctionality and the interplay between MA and integrated sensing, localization, and communications, covering MA for joint sensing and communications, multimodal sensing-aided communications, multimodal sensing and digital twin-assisted communications, and communication-aided sensing/localization systems. We finish with studying MA for emerging intelligent applications such as semantic communications (SeComs), virtual reality (VR), and smart radio and reconfigurable intelligent surfaces (RISs), before presenting a roadmap toward 6G standardization. Throughout the text, we also point out numerous directions that are promising for future research.

Original languageEnglish
Article number10562043
Pages (from-to)1-48
Number of pages48
JournalProceedings of the IEEE
DOIs
Publication statusPublished - 18 Jun 2024

Keywords

  • 6G
  • 6G mobile communication
  • Artificial intelligence
  • artificial intelligence (AI)
  • augmented reality (AR)
  • code-domain multiple access (CD-MA)
  • integrated sensing and communications (ISACs)
  • Internet of Things (IoT)
  • machine learning (ML)
  • Multiaccess communication
  • multiple access (MA)
  • NOMA
  • nonorthogonal multiple access (NOMA)
  • orthogonal multiple access (OMA)
  • rate-splitting multiple access (RSMA)
  • reconfigurable intelligent surfaces (RISs)
  • semantic communications (SeComs)
  • Sensors
  • space-division multiple access (SDMA)
  • universal multiple access (UMA)
  • Wireless networks
  • Wireless sensor networks

ASJC Scopus subject areas

  • General Computer Science
  • Electrical and Electronic Engineering

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