Virtualizing RAN: Science, Strategy, and Architecture of Software-Defined Mobile Networks

2025-06-11

AI Summary

Current RAN virtualization research often treats spectrum policy, cloud engineering, and organizational readiness in isolation, lacking cross-disciplinary integration. This paper proposes a holistic vRAN framework targeting 5G cost reduction and 6G AI-native evolution, uniquely integrating four dimensions: spectrum science, cloud-native engineering, business strategy, and organizational culture. Methodologically, we (1) develop an empirical performance model linking mid-band spectral continuity with software-defined carrier aggregation; (2) derive a spectral-mathematical characterization of vRAN capacity limits; and (3) establish a zero-trust orchestration evaluation framework incorporating security overhead. Technically, the framework leverages O-RAN, digital twins, AI/ML pipelines, NVIDIA EGX, and Samsung vRAN 3.0 edge platforms. Empirical results demonstrate: improved coverage and reduced subscriber churn versus mmWave; inline 256-bit encryption latency of 35–60 μs; and reduction of field-deployment cycle time from 81 to 13 days.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Computer Vision: Generative Adversarial Networks (GANs) for Vision
• Machine Learning: Learning on the Edge & Model Compression

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Search and Retrieval-Augmented AI: Vertical and domain-specific search
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications

Abstract

Virtualising the Radio Access Network (RAN) is widely touted as the corner-stone of affordable 5G and a prerequisite for AI-native 6G. Yet current discourse often isolates spectrum policy, cloud engineering and organisational readiness into silos. This paper delivers an integrated analysis that spans science, technology, business strategy and culture. I first review spectrum-auction economics and show-via a comparative study of T-Mobile US and Verizon-that mid-band contiguity leveraged through software-defined carrier aggregation outperforms mmWave-centric deployments in both coverage and churn metrics. I then formalise the technical foundations of virtualised and open RAN, deriving capacity limits from contiguous and dis-contiguous spectrum maths and quantifying hardware ceilings for 400 MHz mmWave channels. Edge compute platforms (NVIDIA EGX, Samsung vRAN 3.0) and SDN-controlled RAN Intelligent Controllers are examined alongside AI ML pipelines that enable digital-twin-driven optimisation. A security cost model extends recent O-RAN measurements to show how 256-bit cipher enforcement adds 35-60 us latency unless mitigated by inline crypto off-load. Finally, a national automation case study of live vRAN sites -- demonstrates an 81 to 13 day cycle-time reduction once cultural change errors are corrected. I conclude with open research challenges for sub-THz 6G, energy-neutral AI accelerators and zero-trust orchestration, offering actionable recommendations for operators, vendors and researchers.

Problem

• Analyzes spectrum policy and cloud engineering for 5G/6G RAN virtualization
• Evaluates performance of mid-band vs mmWave in coverage and churn metrics
• Examines security, latency, and automation in virtualized RAN deployments

Innovation

• Software-defined carrier aggregation for mid-band
• AI-driven digital-twin optimization in vRAN
• Inline crypto off-load for latency reduction