/ WHERE IT MATTERS

REAL-TIME

REAL-TIME

We use big data to analyse mobile network performance every 15 mins, measuring 4G and 5G network capacity and coverage.

BIG DATA

Big Data

We process this data to provide in- depth analysis and understanding of how networks are performing in any location.

MODELLING

MODELLING

DenseWare enables us to visualise network weaknesses, provide recommended small cell deployment locations and predicts improvements to end users.

REAL-TIME

BIG DATA

MODELLING

PINPOINTING OPTIMAL DEPLOYMENT LOCATIONS

 

Dense Air analyses network performance on a building by building basis using Big Data and our Network Quality Test (NQT) application, providing recommended locations for the deployment of small cells via our Denseware portal.

USER FRUSTRATION

AT THEIR DESK, HAVING DINNER OR ATTENDING A CONCERT

Poor indoor mobile coverage or network congestion is frustrating to operators and end users. Applications fail to work, destroying the smart phone experience and prevents people getting the “Work, Rest and Play” experience they pay for.

REAL-TIME INSIGHTS

COUNTRY BY COUNTRY, BUILDING BY BUILDING

Dense Air big data analysis is based on measured network performance from the end user perspective. This differs dramatically from the traditional Macro cell view that Mobile Operators take. End users care about their personal experience – how networks perform to suit their needs.

OUR ANALYSIS

ARTIFICIAL INTELLIGENCE & MACHINE LEARNING

Algorithms that predict network improvement are built into the heart of DenseWare. We allow end user and mobile operators to see the impact of densification and network extension, that includes the improvement in end user experience, and even download and upload speeds.

MEASURE, ANALYSE, PREDICT, DEPLOY

REMOVING THE GUESS WORK

The economics of small cell deployment are critically dependant on placing the small cells in the right location, indoor and outdoors, and configured in the right way (i.e. with Wired or Relay based backhaul). DenseWare takes the guess work out of the equation. 

UNDERSTANDING NETWORK LIFECYCLES

DenseWare analysis is available via an internet portal, providing specific results that allow our clients and potentially end users to identify the improvements that can be made to the network using small cells, street by street, building by building, and even country by country. Users can also view where Dense Air have already deployed small cell assets that can be rapidly activated, using the Neutral Host capabilities, to improve network performance.

INFORMED NETWORK ENHANCEMENT

Denseware and NQT is a holistic suite of tools that informs where investment is needed and how targeted deployment of small cells running on dedicated spectrum can drastically improve end user experience, while at the same time improve the overall network efficiencies and ultimately the cost per bit of any mobile network.

Determine Expected Network Performance in any location. Globally

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Identify Target Areas
Denseware aids operators in improving network coverage and capacity. Understanding how the network performs, taking into account the location of existing macro sites, volume of users the site serves and the topology of the environment enables Denseware to make real-world recommendations for where to deploy small cells.
Applied Machine Learning
Denseware performs Machine Learning to model end user experience and behaviour such as areas of high footfall, voice calls, peak usage areas and/or locations. Denseware combines this knowledge with data from multiple sources, such as macro cell locations, ducting maps and locations of street furniture to model the deployment of small cells, and optimise the construction of the network.
Pre-Deployment Network Characteristics
Critical to the deployment of small cells is to do so ‘Where It Matters’. With access to multiple datasets from user handsets uploading billions of KPI’s our analytics tools can precisely map the performance of each operators network – Country by Country, Street by Street and Building by Building.
Calculate Network Improvements

In modelling the expected outcome of small cell deployments, Denseware allows operators to be much more efficient in how they expand or improve their network.

Denseware can predict the improvement a single small cell may have when deployed using UE Relay in cell edge conditions, or with a dedicated Fibre backhaul.  It can also factor in the improvement this small cell will make to the surrounding Macro network, by reducing the load and increasing spectral efficiency. 

Combined Metrics to provide insight into End User Experience

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How NQT Works
We simulate the behaviors of typical smart phone applications, and measure the response and ability of a mobile network to deliver the connectivity required (download and upload, latency, jitter and responsiveness).

Rather than relying on traditional network parameters such as SINR, RSRP and throughputs as a gauge of network performance, our indicators measure end user experience at application level – providing a more valuable insight into Quality of Experience (QoE).

NQT Score

As NQT carries out various tests during its cycle it will assign different NQT scores based on the ability for the network to supporting different interactions, such as streaming video, making a call or uploading content to the web. These scores are shown using a simple colour scheme which means:

 

Grey: score of less than 1.0 means your “smartphone apps basically don’t work…”

Red: score of 1.0 to 2.0 means your “smartphone apps work poorly, some will, some won’t…”

Orange: score of 2.0 to 3.0 means your “smartphone apps all work, but some take longer to respond…”

Yellow: score of 3.0 to 4.0 means your “smartphone apps all work well, as intended, like Green: you are connected to a super fast Wi-Fi network”

Green: score of 4.0 to 5.0 means your “smartphone apps all work as well as is possible… Perfect network performance”

From the Ground to the Cloud
Test results are provided to the end user using a colour-coded scale for ease of understanding. However the test data – traditional radio conditions KPIs – is also sent back to the cloud to be proceeded by Denseware.

For operators this means that with more people testing, providing network insights, the more informed they can be about future deployment decisions.

NQT Denseware Cycle
Every test that the NQT app makes is uploaded into DenseWare servers and included in our big data analysis. This allows us to rapidly characterize the existing radio conditions and end user QoE.

Using this data we can then predict the network improvement that can be made through the deployment of one or more small cells. This cycle of test, deploy, analyse accelerates the machine learning process, fine tuning future network deployments and creating a more cost effective, responsive and agile network.

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