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High-performance networks that adapt to your business demands

Boost ROI & user experience with AI planning & Optimization

Network optimization

Mobile networks are growing more expansive and complex. With infinite 5G opportunities on the horizon, communication service providers (CSPs) can gain an edge through AI-powered, data-driven network optimization technologies - maximizing both the network's performance and potential, while intuitively delivering on strategic objectives amidst growing scale and complexity.

What is network optimization?

Network optimization is achieved by applying industry-leading, AI-powered technologies throughout the network lifecycle to align network performance with strategic objectives and maximize return on investment.

Leveraging live and predictive network data, network optimization technologies push the network to its maximum potential, proactively resolving performance issues ahead of subscriber impact. Through active monitoring and predictive forecasting, network planning technologies evaluate future network demands and identify where and when to expand capacity for maximum returns, months in advance.

This results in an always-on, high-performing network – tailored to strategic business objectives and ready to meet increasingly critical performance demands of future 5G use cases.

Mission critical network slicing

Four steps of network optimization



To capture the value of the 5G era, CSPs must be ready to adapt to the constantly changing demands and expectations of emerging 5G use cases, for consumers & enterprises alike.



Network benchmark criteria are growing more expansive and dynamic. CSPs must identify which key metrics to focus on and how to evaluate them proactively and effectively.



AI-powered technologies identify gaps where key metrics fall short, drill-down to the root cause and proactively resolve the issue across the full end-to-end network.



With traffic forecasting and performance prediction, network optimization becomes integral to network investment planning – identifying critical congestion areas that cannot be solved with optimization.

Learn. Improve. Repeat.

Reinforcement learning empowers CSPs to integrate business strategy within the network – proactively delivering on business-defined KPIs such as user experience and transmission power efficiency. Learn how in our latest case with MásMóvil and Swisscom.

Read the case

Benefits of network optimization

Network optimization is effective in boosting network investment returns, while ensuring superior network experience and easier network operations, without the need for capacity expansion. As validated in our engagements with frontrunners like Swisscom, TDC and other leading CSPs, network optimization is proven to produce many direct and indirect benefits on both network and business performance.


Maximize ROI

  • 31% reduction of cells with poor spectral efficiency
  • 15% increase in downlink user throughput during busy hours
  • 10% reduction in unplanned carrier expansions


Improve user experience

  • 15% user experience improvements

  • 20% increase in deployment capacity

  • 70% reduction in customer complaints

  • 90% external benchmark wins


Future-proof operations

  • 4x larger network managed with the same team
  • 50% faster site acceptance
  • 3.4% decrease in site power consumption
The virtual drive test

With real traffic data and AI-powered geolocation, today’s service providers can remotely analyze, tune and optimize network equipment – reducing network rollout carbon emissions to nearly zero, speeding up site acceptance and driving a better subscriber experience.

Read the case

5G and network optimization

5G is rewriting the playbook for mobile networks – bringing more applications, devices, spectrum, energy and expenses into network operations. This is generating thousands of new consumer, enterprise, and mission-critical use cases, all with complex requirements and placing increased pressure on network performance.

In this new reality of constant change and complex service level agreements (SLAs), a properly designed network which intuitively aligns with strategic objectives while maintaining a low total cost of ownership becomes more important than ever, serving as the main foundation not only to meet increasingly challenging use case demands and deliver on SLAs, but also ensure long-term business success.

Industry robots automation automotive manufacturing
People using devices in public transport

AI, data and network optimization

Just as AI and data are key to winning with 5G, multi-dimensional data sources are key to winning with network optimization. If you can’t measure it, you can’t improve it – which is why network optimization technologies rely on a varied range of data sources including data from the network itself, but also third-party data such as benchmark campaigns or crowdsourced data. Together, this ensures a full end-to-end perspective of the network’s performance against the assigned strategic objectives, which gets harder every day as the better the network performance, the more difficult it can be to achieve performance gains.

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It’s not technology holding AI back, it’s humans. Find out why explainable AI is key to creating a healthy AI culture in today’s businesses.

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How to measure network optimization

Network optimization metrics are divided into two main areas: network-centric resource KPIs (R-KPI) and use-case-centric service KPIs (S-KPI).


Network-centric resource KPIs

R-KPIs are the primary metric of most traditional forms of network optimization. With this approach, KPIs are typically specified per each network domain (such as radio networks, transport networks, core networks, and IP multimedia subsystems (IMS)). They are measured based on the performance of individual network elements such as network accessibility (whether a call can be established), retainability (whether calls are dropped) and integrity/quality (download speed).



Use-case-centric service KPIs

S-KPIs frame end-to-end network performance in ways suitable to deliver on both consumer expectations such as video resolution, video stalls, web access time, VR gaming latency, and over-the-top (OTT) voice mean opinion score, as well as enterprise requirements such as latency, jitter, and availability. A critical requirement for this approach is end-user specific data such as net promoter score, complaints, crowdsourced data, call trace records. It is also critical that this data is proactively monitored and acted upon, for example data from customer call centers can be correlated with network data to derive customer perception of network performance. However, access is increasingly difficult and expensive, as data is spread across various systems, and is sometimes limited by encryption or privacy regulations (e.g., GDPR, iOS).

“Excellent network performance and user experience can be achieved using innovative cloud-native solutions that combine AI, big data and the expertise of network engineers. Ericsson Network Design & Optimization is leveraging these capabilities to provide services and software that enable CSPs to support the opportunities 5G presents and to meet the needs of the end-customers.” Adaora Okeleke Principal Analyst, Service Provider Operations & IT

Network optimization solutions

Network optimization is achieved through a combination of cognitive software technologies which are uniquely developed and applied by software engineers and data scientists across the full end-to-end network and the various lifecycle stages of planning, design, tuning and continuous optimization.

Ericsson currently deploys its leading network optimization solutions across nine million live network cells globally where we continue to propel the world’s best networks, including many frontrunner commercial 5G networks, to their optimal potential.

Ericsson’s cognitive software solutions are fully automated, proactive and precision engineered for high-performance network operations based on live- and historical network data. In addition to generating superior network performance, this is also proven to lower our customers operational costs and network footprint, as well as offering the highest possible return on network investments.


Network Planning

Our AI-powered solutions result in smarter capital expenditure (capex) through improved prediction accuracy, greater return on investment and superior user experience.


Network Design

We enable our customers to build their networks with greater precision, making them ready to deliver new use cases for both consumers and enterprises, at the right cost.


Network Tuning

We deliver a faster time to market for our customers with AI-powered network tuning that ensures faster validation of quality for a successful commercial launch.


Network Optimization

We empower our customers to continually maximize performance, efficiency and profit gains across their full end-to-end network chain – delivering benchmark network experiences at the lowest possible TCO.

Ericsson network optimization

Through industry-leading AI technologies, highly skilled global experts with the unique ability to go off-script and uncover innovative solutions to unparalleled issues and in partnership with our customers, we make the best networks better.

Explore our solutions

Trending insights

Boost ROI & user experience with AI planning & optimization

For Communication Service Providers (CSPs) to capitalize on their ongoing investments in 5G, they must transform how they plan, design and optimize their networks. CSPs that take a data driven approach to these operations whilst leveraging modern IT practices will be well placed to generate a strong return on investment (ROI) for 5G while meeting customer demands for better user experience.

Network experience: Why performance partnerships are crucial

Telecom is entering a new era, where technology partnerships will be key to unleashing the rapid innovation of 5G. This is something that Vodafone and Ericsson have been doing for quite some time – from driving Artificial Intelligence and new cognitive network design and optimization capabilities, to delivering new techniques to understand and improve network performance.

AI: enhancing customer experience in a complex 5G world

Reinforcement learning enables a network to continuously learn from observations and experiences, maintaining an optimized customer experience in a dynamic environment, as validated in two live networks.

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