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.
Many manual tasks yield to high time investment
Manual tasks lead to inconsistency and inaccuracy
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.
Many actions are manual and repetitive
Low added value engineering time
10%
Less interference
90%
Accuracy level
100%
Consistency level
90%
Reduction in manual effort
Get started and request a demo to learn how RF Shaping can help you.
Below you will find answers to the most common questions about RF Shaping.
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.
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.
Get started and request a demo to learn how RF Shaping can help you.
