CellOS: Zero-touch Softwarized Open Cellular Networks

Abstract

Current cellular networks rely on closed and inflexible infrastructure tightly controlled by a handful of vendors. Their configuration requires vendor support and lengthy manual operations, which prevent Telco Operators (TOs) from unlocking the full network potential and from performing fine grained performance optimization, especially on a per-user basis. To address these key issues, this paper introduces CellOS, a fully automated optimization and management framework for cellular networks that requires negligible intervention ("zero-touch"). CellOS leverages softwarization and automatic optimization principles to bridge Software-Defined Networking (SDN) and cross-layer optimization. Unlike state-of-the-art SDN-inspired solutions for cellular networking, CellOS: (i) Hides low-level network details through a general virtual network abstraction; (ii) allows TOs to define high-level control objectives to dictate the desired network behavior without requiring knowledge of optimization techniques, and (iii) automatically generates and executes distributed control programs for simultaneous optimization of heterogeneous control objectives on multiple network slices. CellOS has been implemented and evaluated on an indoor testbed with two different LTE-compliant implementations: OpenAirInterface and srsLTE. We further demonstrated CellOS capabilities on the long-range outdoor POWDER-RENEW PAWR 5G platform. Results from scenarios with multiple base stations and users show that CellOS is platform-independent and self-adapts to diverse network deployments. Our investigation shows that CellOS outperforms existing solutions on key metrics, including throughput (up to 86% improvement), energy efficiency (up to 84%) and fairness (up to 29%).

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Cited by in corpus (6)

• Open, Programmable, and Virtualized 5G Networks: State-of-the-Art and the Road Ahead
• Sl-EDGE: Network Slicing at the Edge
• SteaLTE: Private 5G Cellular Connectivity as a Service with Full-stack Wireless Steganography
• Intelligence and Learning in O-RAN for Data-driven NextG Cellular Networks
• Choose, not Hoard: Information-to-Model Matching for Artificial Intelligence in O-RAN
• Streaming from the Air: Enabling Drone-sourced Video Streaming Applications on 5G Open-RAN Architectures