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AI for network efficiency

Augment human intelligence to improve decision making & increase network efficiency

One of the most important concerns for many Chief Technology Officers (CTOs) and Chief Financial Officers (CFOs) is finding the most effective ways to build network capacity in line with projected growth in demand.

Network complexity will explode in the next five years as the roll out of 5G accelerates and many CSPs refresh their LTE networks. Networks are expected to grow by 73% in the next five years, more than five times the rate seen in the last five years. Yet budgets remain flat and CTOs need to do more with less. Telco AI can maximize existing assets and help plan CAPEX in the right places.

A future-proof network evolution plan must be innovative and reliable enough to support new services, business models and use cases as they arise. However, before new CAPEX investments are made, it’s important to maximize the assets on the ground and understand exactly the best areas to make network investments that add the most capability to launch new 5G services and win the highest returns.
 

How can telcos increase network efficiency with Cognitive Radio Frequency Analytics

 

Radio Frequency (RF) optimization is the most important way to guide CSP investments in coverage and quality to deliver the highest quality of experience (QoE) for customers. To guide their investment decisions, CTOs need a more detailed view of network performance than is possible with conventional drive testing and geolocation tools.

How can CSPs use Spectrum to optimize network efficiency?

Spectrum is one of a CSP’s most valuable resources, as well as one of its most expensive. Making use of finite spectrum is paramount and network investments that focus on the efficient use of spectrum are the most likely to achieve the biggest returns. Conventionally, CSPs have relied on analyzing cells with low average capacity performance indicators at peak traffic times. 

How can Nokia Spectral Performance Analysis improve network data capacity?

A more effective approach is the Nokia Spectral Performance Analysis. Instead of simply analyzing individual cells, the service divides cells into multiple zones with similar characteristics, measures the spectral efficiency for each zone and automatically recommends ways to improve network data capacity. AI makes the analysis more granular, so CAPEX investments can be more precise and bring a higher ROI. 
 

case study

Spectral Performance Analysis for better customer experience

How to improve network Quality of Service and CAPEX

 
Nokia collects, stores and analyzes data from multiple sources, including Minimization of Drive Test (MDT) data. MDT allows performance data to be collected from Nokia and other vendor networks, tapping into billions of anonymized measurement reports sent by ordinary mobile phones.

Optimize RF coverage by identifying coverage gaps and interference, enabling CSPs to prioritize improvement spending.

80%

lower cost than manual drive testing

100%

CAPEX savings against legacy geolocation tools

80%

faster network optimization
 

Case studies: how we helped our customers optimize their network efficiency

 

Hutchinson 3 Indonesia wanted to better understand how its increasingly complex network was performing and make improvements to create a better experience for its subscribers. With its AI-driven solution Nokia delivered the following benefits:

17%

higher spectral efficiency
 

60%

faster optimization through automation

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