The emerging demands of sixth-generation wireless networks, such as ultra-connectivity, native intelligence, and cross-domain convergence, are bringing renewed focus to cooperative non-orthogonal multiple access (C-NOMA) as a fundamental enabler of scalable, efficient, and intelligent communication systems. C-NOMA builds on the core benefits of NOMA by leveraging user cooperation and relay strategies to enhance spectral efficiency, coverage, and energy performance. This article presents a unified and forward-looking survey on the integration of C-NOMA with key enabling technologies, including radio frequency energy harvesting, cognitive radio networks, reconfigurable intelligent surfaces, space-air-ground integrated networks, and integrated sensing and communication-assisted semantic communication. Foundational principles and relaying protocols are first introduced to establish the technical relevance of C-NOMA. Then, a focused investigation is conducted into protocol-level synergies, architectural models, and deployment strategies across these technologies. Beyond integration, this article emphasizes the orchestration of C-NOMA across future application domains such as digital twins, extended reality, and e-health. In addition, it provides an extensive and in-depth review of recent literature, categorized by relaying schemes, system models, performance metrics, and optimization paradigms, including model-based, heuristic, and AI-driven approaches. Finally, open challenges and future research directions are outlined, spanning standardization, security, and cross-layer design, positioning C-NOMA as a key pillar of intelligent next-generation network architectures.

翻译：第六代无线网络对超连接、原生智能和跨域融合等新兴需求，正使协作非正交多址接入（C-NOMA）作为可扩展、高效和智能通信系统的关键使能技术重新成为研究焦点。C-NOMA在NOMA核心优势的基础上，通过利用用户协作和中继策略来提升频谱效率、覆盖范围和能源性能。本文对C-NOMA与射频能量收集、认知无线电网络、可重构智能表面、空天地一体化网络以及集成感知与通信辅助的语义通信等关键使能技术的融合进行了统一且前瞻性的综述。首先介绍了基本原理和中继协议，以确立C-NOMA的技术关联性。随后，针对这些技术间的协议级协同、架构模型和部署策略进行了重点探讨。除技术融合外，本文还强调了C-NOMA在数字孪生、扩展现实和电子健康等未来应用领域中的协同编排。此外，文章对近期文献进行了广泛而深入的回顾，按中继方案、系统模型、性能指标和优化范式（包括基于模型、启发式和人工智能驱动的方法）进行分类梳理。最后，本文概述了标准化、安全性和跨层设计等方面的开放挑战与未来研究方向，将C-NOMA定位为智能下一代网络架构的关键支柱。