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.

翻译：多址接入（MA）是任何无线系统的关键组成部分，指利用资源维度以最高效的方式服务多个用户/设备/机器/服务的技术。鉴于多功能无线网络对通信、感知、定位、计算一体化需求，以及机器学习/人工智能（AI）在无线网络中的蓬勃发展，MA技术预计将在6G及未来迎来范式转变。本文对过去、新兴及未来的MA技术进行了教程式介绍、综述与展望，特别关注无线网络智能化和多功能性如何引发对这些技术的重新思考。文章首先概述了正交多址、物理层多播、空域多址、功率域多址、速率分割多址、码域多址及其他域的多址技术，并强调了通过提供跨所有资源维度的MA方案统一认知来推动通用多址研究（缩减而非扩展MA方案知识树）的重要性。随后深入探讨无线网络智能化时代对MA方案的重新审视，涵盖面向MA的AI技术（如AI赋能的资源分配、优化、信道估计、接收机设计、用户行为预测）以及面向AI的MA技术（如联邦学习/边缘智能与空中计算）。接着讨论MA对网络多功能性的支撑及MA与集成感知、定位、通信之间的相互作用。最后在提出6G标准化路线图之前，研究了面向新兴智能应用的MA技术，并指出了诸多具有前景的未来研究方向。