UMP WiFi Optimization

Bring your customer WiFi experience to the next level

In the era of competition for customers, Service Providers constantly innovate their infrastructure, bandwidth and OTT (Over The Top) services. However, with bad WiFi experience the customer will not be satisfied with nor enthusiastic about any additional charges for Internet access or OTT services. To solve this problem, AVSystem came up with the idea of the UMP WiFi Optimization, so that you can always provide the best customer WiFi experience.

The need for a WiFi experience management solution

  • 1

    Most popular WiFi band is overpopulated

    WiFi 2.4 GHz is still the most widely used WiFi frequency band. Unfortunately, it is not perfect — Its main problem is signal quality suffering from the widespread use of this band. Whenever multiple transmitting (neighboring routers, bluetooth devices, microwaves) and receiving (phones and laptops) devices are competing for the same bandwidth, the physical WiFi signal in the air gets distorted and loses its range as well as data capacity.

  • 2

    Existing channel management solutions are insufficient

    WiFi standard specifies multiple channels (frequency ranges), so it’s important for a device to select the right channel to reduce channel contention. While most of the routers offer auto-channel selection capabilities, there are various problems, such as the fact that the vendor-specific implementation is not easy to verify and lacks information about neighboring routers configuration. It also offers little performance metrics and no analytics or historical data whatsoever.

  • 3

    WiFi experience management is critical for Service Providers business

    Once the customer calls with complaints about his recurring WiFi performance issues, there is not much that a customer care operator can do to improve the customer experience. In consequence, the dissatisfied customer loses trust in the quality of Service Provider’s offer. Things would be different, however, if only the operator had access to the UMP WiFi Optimization solution!

UMP WiFi Optimization

The WiFi Optimization solution is a flagship UMP monitoring module aimed at improving customer WiFi experience. It offers crucial insight into customer WiFi experience over time and features an algorithm that accurately chooses the best WiFi channel based on a whole population of all routers managed by the platform instead of industry-standard single device algorithm. UMP WiFi Optimization stands apart from competition in many additional ways.

  • Let Machine Learning and Artificial Intelligence predict future issues for you

    The WiFi Optimization solution integrates with state-of-the-art streaming engine gathering the data directly from device hardware WiFi chip instead of CWMP data model — it features Machine Learning and Artificial Intelligence for time series forecasting which enables alerting even before the performance starts to degrade.

  • Accurately visualize customer WiFi experience with Key Performance Indicators

    The WiFi Optimization analytics were designed not only to visualize one managed router, but the full network graph of all routers within one another’s reach. It can group devices by signal strength and channel rank algorithm, as well as present Key Performance Indicators such as Signal to Noise Ratio (SNR) for both single devices and groups of them.

Instantly react to WiFi alerts using Smart Workflows Instantly react to WiFi alerts using Smart Workflows

Not only are alerts raised when the performance metric threshold is reached, but also the operator can immediately perform repair action due to the Smart Workflows integration. The WiFi repair actions can also be executed automatically — dramatically optimizing the costs of ISP’s Customer Care.

Key features

  • Analytics presented as timelines of important WiFi Key Performance Indicators (KPIs) such as signal strength, signal to noise ratio (SNR), downlink retransmissions and failures, downlink/uplink bandwidth availability and consumption, channel swaps, channel rank score and many more
  • Channel ranking algorithm based on extensive research and WiFi transmission physical signal studies with an algorithm based on a whole population of all routers managed by the platform
  • Several ways of visualizing customer WiFi experience: all devices grouped by signal strength or channel rank algorithm score and a graph of all SSIDs visible by routers connected to the UMP system
  • Alerting — both historical and ongoing (when performance metric threshold is reached) along with an ability to instantly solve the root issue using the Smart Workflows integration
  • State-of-the-art monitoring data streaming engine integration allowing for very frequent (every few minutes) data sampling directly from device hardware WiFi chip instead of CWMP data model and featuring Machine Learning and Artificial Intelligence for fault prediction
Download the full version of the document
Thank you.
Enjoy reading!

If the download doesn't start automatically in a few seconds, please click here to access the document directly.

AVSystem sp. z o.o., Radzikowskiego 47D, Cracow is the controller of your personal data. If you agree to a specific communication channel, we will process your personal data for marketing purposes. You can withdraw your consent at any time or object to data processing. You have the right to access your personal data, the right to rectification data, the right to erasure data, the right to demand the restriction of the processing of your personal data and the right to object to the processing of your data. More information about processing of your personal data is available here.

Let's talk!

If you'd like to talk to our sales team about our products, go to the contact form or write to us directly at [email protected].

back icon

This website is using cookies

We use cookies for statistical and marketing purposes and to improve the quality of our services. The information stored in cookies usually allow the identification of a specific device or user’s browser, so they may contain personal data. By continuing to use this website with setting the web browser in a way which alows the use of cookies by the website means your’s consent to the use of cookies. You can change your web browser settings at any time.
More information on the processing of personal data and cookies you can find in our Privacy and cookies policy.