Wireless communication systems to date primarily rely on the orthogonality of resources to facilitate the design and implementation, from user access to data transmission. Emerging applications and scenarios in the sixth generation (6G) wireless systems will require massive connectivity and transmission of a deluge of data, which calls for more flexibility in the design concept that goes beyond orthogonality. Furthermore, recent advances in signal processing and learning have attracted considerable attention, as they provide promising approaches to various complex and previously intractable problems of signal processing in many fields. This article provides an overview of research efforts to date in the field of signal processing and learning for next-generation multiple access, with an emphasis on massive random access and non-orthogonal multiple access. The promising interplay with new technologies and the challenges in learning-based NGMA are discussed.

翻译：无线通信系统至今主要依赖资源的正交性来简化从用户接入到数据传输的设计与实现。第六代（6G）无线系统的新兴应用与场景将需要海量连接和大量数据传输，这要求设计理念超越正交性，具备更高的灵活性。此外，信号处理与学习领域的最新进展引起了广泛关注，为处理许多领域中复杂且先前难以解决的信号处理问题提供了有前景的方法。本文概述了面向下一代多址接入的信号处理与学习领域迄今的研究成果，重点聚焦于大规模随机接入和非正交多址接入。同时，讨论了与新技术的协同潜力以及基于学习的下一代多址接入所面临的挑战。