A Comprehensive Tutorial and Survey of O-RAN: Exploring Slicing-aware Architecture, Deployment Options, Use Cases, and Challenges
Not on the map. Why?
Abstract (arXiv)
Open-radio access network (O-RAN) seeks to establish the principles of openness, programmability, automation, intelligence, and hardware-software disaggregation with interoperable and standard-compliant interfaces. It advocates for multi-vendorism and multi-stakeholderism within a cloudified and virtualized wireless infrastructure, aimed at enhancing the deployment, operation, and management of RAN architecture. These enhancements promise increased flexibility, performance optimization, service innovation, energy efficiency, and cost effectiveness across fifth-generation (5G), sixth-generation (6G), and beyond networks. A silent feature of O-RAN architecture is its support for network slicing, which entails interaction with other domains of the cellular network, notably the transport network (TN) and the core network (CN), to realize end-to-end (E2E) network slicing. The study of this feature requires exploring the stances and contributions of diverse standards development organizations (SDOs). In this context, we note that despite the ongoing industrial deployments and standardization efforts, the research and standardization communities have yet to comprehensively address network slicing in O-RAN. To address this gap, this paper provides a comprehensive exploration of network slicing in O-RAN through an in-depth review of specification documents from O-RAN Alliance and research papers from leading industry and academic institutions. The paper commences with an overview of the relevant standardization and open source contributions, subsequently delving into the latest O-RAN architecture with an emphasis on its slicing aspects. Furthermore, the paper explores O-RAN deployment scenarios, examining options for the deployment and orchestration of RAN and TN slice subnets. It also discusses the slicing of the underlying infrastructure and provides an overview of various use cases related...
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 May 2024.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2025: 3; 2026: 4.
7 papers.
- 2025AI-Native Open RAN for Non-Terrestrial Networks: An Overviewcited by 1
- 2025Task Specific Sharpness Aware O-RAN Resource Management using Multi Agent Reinforcement Learningcited by 1
- 2026Agentic AI-RAN: Enabling Intent-Driven, Explainable and Self-Evolving Open RAN Intelligencecited by 1
- 2025AI-Open-RAN for Non-Terrestrial Networkscited by 0
- 2026Adversarial Attacks in AI-Driven RAN Slicing: SLA Violations and Recoverycited by 0
- 2026Bridging the Cognitive Gap: A Unified Memory Paradigm for 6G Agentic AI-RANcited by 0
- 2026Autonomy in Check: Governor-Mediated Adaptive Security at the Edgecited by 0
- 2026Autonomy in Check: Governor-Mediated Adaptive Security at the Edge16 Sep 2026
- 2026Bridging the Cognitive Gap: A Unified Memory Paradigm for 6G Agentic AI-RAN11 May 2026
- 2026Adversarial Attacks in AI-Driven RAN Slicing: SLA Violations and Recovery1 Apr 2026
- 2026Agentic AI-RAN: Enabling Intent-Driven, Explainable and Self-Evolving Open RAN Intelligence27 Feb 2026
- 2025Task Specific Sharpness Aware O-RAN Resource Management using Multi Agent Reinforcement Learning19 Nov 2025
- 2025AI-Open-RAN for Non-Terrestrial Networks14 Nov 2025
- 2025AI-Native Open RAN for Non-Terrestrial Networks: An Overview16 Jul 2025