Solutions

RF Shaping

Field-proven AI reinforcement learning agent.
Reducing interference while keeping the coverage.

RF Shaping

How to take advantage of your geolocation tool to reduce interferences without affecting coverage?

Many geolocation tools (e.g. ariesoGEO) offer very rich cell-level information about interference, traffic and coverage. However, analysing data points one by one is extremely tedious, so often the analysis remains undone.

manual diagnosis and analysis tasks

Too many manual diagnosis and analysis tasks?

Radio engineers are trying to optimize using their geolocation tool's graphical information cell by cell and not at cluster level. This work is highly manual, which translates into a big waste of time, inconsistency and increased risk of failure.

disadvantage

Many manual tasks yield to high time investment

disadvantage

Manual tasks lead to inconsistency and inaccuracy

Is it feasible to manually handle hundreds of cells for optimizing the whole cluster

Is it feasible to manually handle hundreds of cells for optimizing the whole cluster?

Optimizing a whole cluster manually is huge, since just one cluster can contain hundreds of cells, and each cell's analysis requires a 3-dimensional review (coverage, interference, and traffic) of the cell itself and its neighbors.

disadvantage

Many actions are manual and repetitive

disadvantage

Low added value engineering time

RF Shaping manages automatically all the rich graphical information from your Geo Tool

video rf shaping play video

What benefits can you expect from RF Shaping?

10%

Less interference

90%

Accuracy level

100%

Consistency level

90%

Reduction in manual effort

Clients and partners

t-mobile veon deloitte. tech mahindra telcel softbank amdocs keysight technologies

Get a demo of RF Shaping today

Get started and request a demo to learn how RF Shaping can help you.

Frequently Asked Questions

Below you will find answers to the most common questions about RF Shaping.

How does RF Shaping work?

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RF Shaping reduces the levels of intra-cell interference in urban environments without degrading the coverage, thus improving the network's quality.

RF Shaping utilizes the users geolocalized information as well as the network’s topology, counters and parameters.

RF Shaping uses agents trained with Reinforcement Learning which are able to find improvement opportunities that other methods can't.

How does Tupl Saas work?

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RF Shaping SaaS is delivered in cloud service (e.g. AWS, Azure, etc.) and can also be deployed on-premises, in your private cloud or data center.

It is easy and quick to get started, fit for a faster procurement process, with a functional solution in operation within 2-3 weeks.

Monthly subscription. No strings attached. Stop at any time.

Part of the research behind this solution has been developed together with the University of Málaga as part of the project NEREA, which is funded by the Spanish Ministry of Science and Innovation and the European Regional Development Fund

Spanish Ministry of Science and Innovation and the European Regional Development Fund

Get a demo of RF Shaping today

Get started and request a demo to learn how RF Shaping can help you.

tupl automation by AI for Network Operations

Operations made simple with AI

Associations we belong to:

SmartCity Cluster Tupl O-Ran Alliance Tupl Technology Park of Andalusia Tupl Telecom infra project Tupl 5G Open Innovation Lab Ametic la voz de la industria digital