Sustainable Networks

The Intelligent Operations guide

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Operate intelligently to save energy and improve user experience

It is possible to improve user experience while reducing energy consumption. In this report you will discover the solutions that leading CSPs are implementing in their journey to high performing programmable networks, more autonomous and energy conscious.

Report

Energy cost has become in the last years one of the highest operating costs for communications service providers (CSPs). This makes reducing energy consumption a target for both sustainability and network operation ambitions, and in the long term, a strategic criterion for CSPs evolution plans.

However, many CSPs still hesitate to activate energy-saving software solutions. This is due mainly to the potential risk of impacting traditional network performance indicators and the complexity of the features configuration. With the traditional approach, CSPs will not be able to control energy consumption to achieve their targets, so they need to evolve how to plan, deploy, and run mobile networks.

“Sustainability and energy efficiency are key for designing mobile networks today. The programmability of the high-performing network will enable its evolution into an intent-driven, autonomous system, capable of supporting diverse service needs. This transformation will be powered by AI”.

- Erik Ekudden, Chief Technology Office, Ericsson

To achieve optimal performance, CSPs aim to adjust installed capacity to real-time traffic demand without affecting user experience. Network capacity is typically deployed to handle peak traffic during the busiest hours, resulting in over-capacity for most of the day. Software functionality is employed to align network capacity with traffic demand. The challenge lies in transitioning from individually tuned energy-saving features to an orchestrated approach that allows the network to follow the capacity demand curve, delivering the desired performance without wasting energy or requiring additional hardware. The main challenges for energy performance optimization are:

Securing performance levels while executing energy saving features

Many CSPs today successfully use energy saving software to make significant energy and opex savings in their networks. Though, to preserve network KPIs, in most networks the functionality is not used to its fullest potential. In addition, the user experience depends on a combination of network performance and the applications running in the user equipment. To increase the energy savings with secured performance levels in the RAN require enhanced capabilities such as observability and service awareness, with user experience in focus.

Energy counters not available in old equipment

Observability is a vital factor to optimize energy performance and requires information about performance indicators and energy use from multiple network parts. The availability and accuracy of both counters and data collection pose a challenge where older equipment may not have compatible counters, making pertinent data collection difficult with a need to complement the data with indirect measurements for instance based on estimates of energy consumption values. Additionally, there is an inherent challenge in balancing the granularity of energy data. As an example, energy meters may only provide site level understanding of energy consumption, and this level of granularity does not provide actionable information that can be used to effectively manage energy consumption.

Fixed and static settings increase operation complexity

The data traffic in a specific radio base station site varies largely with daily, weekly, and seasonally variations. Also, the location of a site has large impact on the traffic levels and variations. The dynamics in traffic make it challenging to use fixed settings and thresholds in energy saving features to the secure both the performance levels and to achieve optimal energy savings for each site. By applying insights from network data, sites and service areas can be segmented into different categories, each with its own settings and thresholds. This will help improve performance levels and savings. The challenge to realize these improvements lies in the enhanced operational complexity as the settings require manual handling and follow-up which may become an obstacle for an effective implementation.

Interoperability and orchestration between different energy-saving solutions ensuring the best selection for every scenario

Ericsson and other vendors are providing a great number of energy-saving solutions to support service provider’s ambition to save energy. The increasing number of solutions provide a large variety in how to combine functionality that switch off parts of equipment, complete frequency bands and equipment, as well different levels of sleep with varying reactivation times. The challenge is further increased by the complexity of alternatives for different radio access generations and frequency layers. Without interoperability and orchestration between the different energy saving solutions it is difficult to ensure the best selection of features to achieve the largest energy savings for each scenario.

Ericsson is addressing the energy challenge for CSPs by providing a range of automated energy solutions tailored to their specific needs, transforming RAN energy management to be more intelligent and transparent. These solutions are designed to be future-proof, ensuring seamless evolution and adaptation of the network platform over time. This approach allows CSPs to reduce energy consumption while maintaining high network performance and user experience, enabling energy performance optimization.

Ericsson’s holistic solution for automation relies on both distributed real-time and centralized non-real-time automation. Moving beyond self-optimization networks (SON) architecture towards intent-driven architecture of programmable networks.

In the figure below, we show at the left solutions in the SON architecture and at the right in the Open RAN architecture.

Service Continuity: Intelligent RAN Power Saving solution is part of the Service Continuity suit also known as AI-apps. This service aims to pre-empt and predict events in CSP networks to act before they occur.

Predictive Cell Energy Management: Predictive Cell Energy Management (PCEM) is an innovative solution that minimizes radio access network (RAN) energy consumption across multivendor environments. Using advanced AI techniques, PCEM dynamically establishes optimal thresholds that conserve energy without impacting network performance.

Energy Performance Orchestrator rApp: The Energy Performance Orchestrator (EPO) rApp, running on a Service Management and Orchestration (SMO) platform, enables centralized automation to improve energy performance. This setup provides a comprehensive network view and aligns intents across the network. By combining distributed and centralized automation, operators benefit from both a broad network perspective and detailed traffic insights.

RAN Energy Cockpit rApp: This solution provides an energy efficiency map to understand the energy efficiency both at network level and radio node level granularity. Applying AI clustering technology, the sites are classified in different energy efficiency ranks. It monitors the energy efficiency and identifies autonomously the root cause of network inefficiencies.

Site Energy Orchestrator rApp: Ericsson’s Site Energy Orchestration (SEO) is designed to support our customers in addressing the new challenges that come with the transformation in energy generation and consumption.

Automated Energy Saver: Automated Energy Saver (AES) is a functionality implemented in the distributed automation layer in the 5G Advanced SW. AES’s role is to orchestrate the individual energy saving functionality to fulfil an intent.

Optus journey to improve energy performance with automation

Telstra’s commitment: Enhancing user experience with sustainability

DNB is enhancing Malaysia´s 5G network with Automated Energy Saver

Swisscom 5G journey commitment to performance and sustainability

Umniah AI-based solution to improve energy efficiency in Jordan

TDC NET deploys Predictive Cell Energy Management for energy performance

Enable energy performance optimization with high-performing radio networks

Intent-driven automation with AI will secure user experience and reduce energy consumption

Evolving to programmable networks will help CSPs to achieve business and sustainability targets

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Deep dive on energy efficiency

Energy efficiency is on top of CSPs’ agenda – together with the increased capacity demands and the need to address the challenge of exponential data traffic growth. That’s why we are constantly innovating our portfolio and integrate our solutions with renewable energy sources. So, we improve energy efficiency while increasing performance and accelerating the build of nationwide, fully performing 5G.

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