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：迄今，无线通信系统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）无线系统中的新兴应用与场景将需要海量连接与海量数据传输，这要求设计理念突破正交性以具备更高灵活性。此外，信号处理与学习领域的最新进展已引发广泛关注，因其为诸多领域中传统棘手或复杂的信号处理问题提供了极具前景的解决方案。本文综述了当前面向下一代多址接入（NGMA）的信号处理与学习研究进展，重点关注海量随机接入与非正交多址接入。文章探讨了其与新兴技术的前瞻性协同，以及基于学习的NGMA所面临的挑战。