AI RAN | Autonomous Network Optimization

AI RAN Operational Outcomes

Move beyond manual, reactive maintenance. Our AI-native RAN integrates directly into your existing infrastructure to deliver autonomous, self-optimizing network performance that turns growth into a competitive advantage.

It has already been proven at scale at Rakuten Mobile,  with live use cases delivering results.

Predictive Capacity Planning

AI models analyze traffic patterns to predict demand, allowing teams to optimize resources proactively before bottlenecks arise.

Enhanced Spectral Efficiency

Maximize available spectrum through real-time AI-driven optimization, significantly boosting network capacity and user experience.

Intelligent Energy Savings

World-first Level 4 autonomy certification for RAN energy efficiency optimization in Open RAN as validated by TM Forum.

Autonomous Site Management

AI-powered computer vision audits construction and maintenance against design specs, reducing manual site visits and operational burdens.

AI RAN that Leverages Existing Investments

Through our partnership with Intel, we have validated the seamless integration of AI workloads into existing vRAN platform and software stacks, leveraging existing investments and delivering optimized performance. No need for rip and replace or expensive investments in GPU infrastructure.

Proven
vRAN Stack

Deployed at Rakuten Mobile at scale across 10+ million subscribers
Fully virtualized and cloud-native from the ground up
Software-upgradable architecture, with no rip and replace

Efficient AI-RAN
Performance

Seamless AI-RAN integration to leverage existing investments
More reliable uplink detection for lower packet loss
Reduced retransmission and improved efficiency

RAN
Intelligent Controller

Industry’s first nationwide deployment of RIC third-party apps aligned with O-RAN standards.
Dynamic, intent-based network policy
Real-time closed-loop automation

Unified
Data Intelligence

Integrates with Rakuten Site Management portfolio
Real-time KPI analysis and visualization
Operational insights across domains

FAQs

What is an AI-Native RAN and how does it benefit mobile operators?

An AI-Native RAN integrates artificial intelligence directly into all layers of the radio access network architecture, moving from manual, reactive maintenance to autonomous, self-optimizing operations. This allows operators to achieve predictive capacity planning, enhanced spectral efficiency, and automated energy management, turning network growth into a competitive advantage.

Does deploying AI-RAN require a "rip and replace" of existing infrastructure?

No. Rakuten Symphony’s AI-RAN solutions are designed to leverage existing vRAN software stacks. Through our partnership with Intel, we have validated that AI-RAN optimizations can be integrated seamlessly into current vRAN infrastructure, avoiding the need for expensive hardware overhauls or massive GPU investments.

How did Rakuten Mobile achieve Level 4 Autonomy in RAN energy efficiency?

We achieved world-first TM Forum Level 4 Autonomy validation by deploying AI models that perform closed-loop energy optimization. These models predict traffic lulls and automatically adjust network power states, significantly reducing energy consumption without impacting user experience.

What is the role of the RAN Intelligent Controller (RIC) in AI-RAN?

The RIC acts as the brain of the AI-RAN, enabling the deployment of third-party xApps and rApps that align with O-RAN standards. It facilitates dynamic, intent-based network policy and real-time closed-loop automation, allowing the network to make granular performance adjustments autonomously.

How does AI-RAN improve spectral efficiency?

AI-RAN helps improve spectral efficiency by utilizing machine learning to continuously optimize parameters, allowing the network to proactively adjust to unpredictable interference and traffic fluctuations, and manage resource allocation in real-time. AI models help improve reliable coverage and maximize throughput to enable more efficient use of available frequency bands across the network.

How can AI help reduce network deployment time?

AI-native platforms support consistent, large-scale rollout execution by automating manual coordination tasks. Features like AI-powered computer vision for site audits ensure construction matches design specifications, reducing manual site visits and operational burdens, which can accelerate deployment timelines by up to 40%.

What role does AI play in network operations?

GenAI and LLM-powered data platform enables operations teams to interpret large volumes of operational data, automatically correlate network issues, replacing manual triage with rapid insights — compressing decision cycles, accelerating actions, cutting field response time and OPEX, across every layer of the network.

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AI-Native RAN for Mobile Operators Seeking Proven Autonomous Network Optimization

Realize autonomous network performance

AI RAN Operational Outcomes

Latest news and updates

Rakuten Mobile Collaborates with Intel to Forge AI-First vRAN Future

RAN intelligence is a growth strategy, not a cost play