Radio Access Networks (RANs) are engineered to handle peak traffic loads across multiple spectrum layers. However, actual traffic patterns are highly dynamic and often fall below the provisioned capacity, leading to inefficiencies in energy usage.
TCTS introduces an AI-powered approach that dynamically identifies underutilized RAN cells and selectively powers them down or throttles them, without compromising service quality. A built-in Customer Experience (CX) Assurance engine continuously monitors active cells and autonomously reactivates or scales resources as needed.
This closed-loop system ensures optimal spectrum utilization while maintaining superior user experience, delivering measurable improvements in operational efficiency and sustainability.
Navigating the Energy Imperative in Telecom
Telecom operators globally are grappling with the dual challenge of delivering highspeed broadband services while managing escalating energy costs and sustainability mandates.
Key Challenges:
- Rising Energy Costs: Energy prices have surged in recent quarters, with continued volatility expected.
- Sustainability Mandates: Regulatory frameworks such as the UN’s 2030 Agenda for Sustainable Development are driving the need for greener telecom operations.
The urgency for intelligent, real-time energy management solutions has never been greater.
| AI-Enabled Energy Savings of Telcos | ||
| 20-40%* | 73%* | O-RAN |
| of network OPEX is driven by energy consumption | of total energy consumption in mobile networks is attributed to RAN | consumes a significant amount of energy even when there is little or no traffic |
| *Source: GSMA – A blueprint for green networks | ||
Intelligent Automation for Dynamic RAN Optimization
A closed loop platform that leverages proprietary AI algorithms and live traffic analytics to dynamically manage spectrum energization. It integrates seamlessly with existing telecom infrastructure and is designed to be vendor agnostic and deployment flexible. Key capabilities include:
- AI-Driven Spectrum Management: Realtime adaptive control of RAN resources based on traffic and CX metrics.
- Scalable Architecture: Supports up to 320 Gbps downlink throughput per 2U server.
- Optimized for AI/ML: Ingests structured, open datasets for high efficiency machine learning.
- Flexible Deployment: Compatible with COTS hardware, virtual machines, or cloud environments—deployable at core or edge.
- Vendor Agnostic: Operates across multivendor RAN and core setups.
- Non-Intrusive Integration: Supports both mirrored and inline traffic deployments.
- Sustainability by Design: Enables on demand spectrum energization, reducing energy consumption and carbon emissions.
Driving Sustainability, Performance, and Cost Efficiency
By embedding AI-led energy intelligence into the RAN, telecom operators can achieve:
- Up to 40% reduction in RAN energy consumption
- Up to 50% Improvement in network performance
- Enhanced CX via real-time quality monitoring
- Significant OpEx savings through automation
- Intuitive dashboards for real-time visibility and control
This solution enables operators to meet regulatory, operational, and environmental goals while unlocking new efficiencies.
