A Comprehensive Review of Generative AI Applications in 6G

The transition to 6G networks introduces a range of challenges due to increasing complexity, data traffic growth, and the demand for personalized services. Traditional network management techniques are no longer sufficient, as 6G networks require faster speeds, lower latency, and the capacity to support advanced applications. Open Radio Access Networks (O-RAN) offer a flexible architecture that facilitates the integration of hardware and software from diverse vendors, addressing some of these challenges. As networks continue to evolve, AI-driven solutions are becoming essential for ensuring seamless operations and optimizing performance. Generative AI (GAI) is gaining a large attention in 6G networks to solve complex issues such as resource allocation, traffic prediction, and security. Hence, this paper aims to: (a) systematically review existing studies on GAI, focusing on its use cases, opportunities, and challenges, and (b) thoroughly examine both current and potential applications of GAI, analyzing the problems they address, the proposed solutions, and identifying gaps in the existing research.