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.

中文翻译：

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智能多功能 6G 的多种接入技术：教程、调查和 Outlook


多址 （MA） 是任何无线系统的关键部分，是指利用资源维度（例如时间、频率、功率、天线、代码和消息）为多个用户/设备/机器/服务提供服务的技术，理想情况下以最有效的方式。鉴于集成通信、传感、定位和计算对多功能无线网络的需求不断增长，再加上无线网络中机器学习 （ML）/人工智能 （AI） 的激增，预计 MA 技术将在 6G 及以后经历范式转变。在本文中，我们提供了关于过去、新兴和未来 MA 技术的教程、调查和展望，并特别关注无线网络智能和多功能性将如何导致对这些技术的重新思考。本文首先概述了正交、物理层多播、空间域、电源域 （PD）、速率拆分、代码域 MA、其他域中的 MA 和随机访问 （RA），并强调了在通用 MA （UMA） 中进行研究的重要性，通过提供对所有资源维度的 MA 方案的统一理解，来缩小而不是扩大 MA 方案的知识树。然后，它开始重新思考无线网络智能时代的 MA 方案，涵盖 MA 的 AI，例如 AI 赋能的资源分配、优化、信道估计和接收器设计，针对不同的 MA 方案，以及 AI 的 MA，例如联邦学习 （FL）/边缘智能和无线计算 （AirComp）。 然后，我们讨论了网络多功能性的 MA 以及 MA 与集成传感、定位和通信之间的相互作用，包括用于联合传感和通信的 MA、多模态传感辅助通信、多模态传感和数字孪生辅助通信，以及通信辅助传感/定位系统。我们最后学习了新兴智能应用的 MA，例如语义通信 （SeComs）、虚拟现实 （VR）、智能无线电和可重构智能表面 （RIS），然后提出了 6G 标准化路线图。在整个文本中，我们还指出了许多对未来研究有希望的方向。