Cheytec Telecommunications Brings Better Indoor Coverage to the Enterprise using iBwave

Given our ever-growing need for data in today’s world of smart cities, smart buildings and the Internet of Things, the need for fast, reliable connectivity indoors has never been greater. Especially when it comes to the Enterprise.

Traditionally, wireless operators have been the main drivers for deploying indoor wireless networks to Enterprise venues and real estate properties. But with tenant and user demand out-pacing the carrier’s ability to -fund systems, building owners and Enterprise customers are now seeing the value of making capital investments in their properties and meet the demands of their network users.

Meet Cheytec Telecommunications, an iBwave customer whodelivers multi-operator turnkey in-buildng LTE solutions. Cheytec is helping to make an economic shift away from the carrier by expanding the addressable market to include building owners and enterprises. Cheytec does this by working with the wireless operators to bring their spectrum into buildings and leverage a highly developed partner network for both technology and service delivery. Capital investments in LTE coverage made by the building owner enables not just great indoor wireless service, but the opportunity for increased cash flows, higher valuations for property portfolios and new revenue sources. For wireless operators, the in-building system helps extend indoor coverage, densify networks, offer new services to current customers and gain net-new subscribers.

How has iBwave helped?

Designing a multi-carrier indoor wireless networks certainly comes with its fair share of challenges, especially when you are designing for multiple technologies – Small Cells, DAS, and Neutral Host D-RAN(C-RAN), and multiple different venue types.

Previously, Cheytec typically used iBwave to design sports stadiums and transportation hubs – but now they are focusing more on the Enterprise verticals, and with that comes different challenges to overcome. For example, the image on the right shows a heatmap generated in iBwave Design for a 4 story office building which Cheytec used to help select the right solution for this particular venue, accurately assess coverage and capacity requirements and estimate the cost of the entire system.

When using iBwave Design Enterprise, our multi-technology indoor wireless network planning and design platform, Cheytec’s engineers work more productively and can focus simultaneously on multiple projects. The result? Cheytec has reduced their network design process time by an estimated 30%.

Additionally, iBwave expedites the customer approval process significantly as customers recognize that they only use top quality tools and technologies within their designs – and that they have the ability to offer a wide range of in-building technology solutions with multiple design options.

These benefits also lead to reduced time spent on project coordination internally. Because of the speed and flexibility of iBwave Design, it allows Cheytec to accomodate design changes without necessarily altering the project timeline.

“By using iBwave we shorten our response time in terms of delivering a proposal enabling our team to close more deals and generate more revenue.”

José Sangiuliano – Chief Technology Officer, Cheytec Telecommunications

Cheytec’s Favorite iBwave Features

When asked what their favorite features are in iBwave Design, here is what Cheytec said (and why):

Automation of Design Enterprise Networks

With the powerful and intelligent design automation that iBwave provides, design errors are reduced and the time to produce and change designs is accelerated – iBwave also provides them with an efficient way to provide alternative design options for comparative purposes.

3D Predictive Modeling

3D predictive modeling has also been very helpful to Cheytecby providing their customers with a powerful way to visually show the benefits of the proposed solutions and the network performance prediction results, similar to the image on the right showing the 3D model for 40+ story hotel DAS project.

Design and Simulation of Most Cost-Efficient Designs

Also, with the capability to design the entire network using the iBwave database of over 25,000 network components for all wireless technologies, Cheytec is always able to generate a full BOM with Cost Details. This means always being sure they are simulating the most cost-efficient designs, and that their customers have the best design possible for their specific building.

Cheytec’s mission is to deploy the right solution into the right building every time. Using iBwavehas helped them to achieve this consistently.

Conclusion

iBwave has been a key partner for Cheytec by providing a powerful, flexible and comprehensive software solution to provide Enterprise customers and property owners with turnkey LTE solutions that drive value.

Thanks for being such a great customer Cheytec Telecommunications!

Are you an iBwave customer that wants to be featured in our Customer Spotlight series? Send us an email at marketing@ibwave.com

3 Features that Increase Prediction Accuracy

There are many things that can throw off the results of a network’s performance prediction during the design phase of a wireless network deployment. Anything from setting the scale a little bit incorrectly, to using the wrong wall material type, to not knowing what is behind the venue’s walls that may impact signal loss, to using flat surfaces where there are incline surfaces – and the list goes on and on. Needless to say, accurately predicting the performance of a network before it goes live, can be hard to do because so many different factors impact it.

Which is why in iBwave software—both iBwave Wi-Fi and iBwave Design—we try to empower users with many capabilities to ensure that the prediction done in the design phase will be as accurately reflect the performance once it goes live, as accurately as possible.

Here are 3 ways to ensure more accurate prediction results using iBwave software.

The Materials Database and Editor

The out-of-box materials database in iBwave Wi-Fi and iBwave Design is extensive (give or take about 85 different defined materials). But we know that all the materials in the default database are the only ones that may be needed during the design of a network. It is often the case that our customers need to add custom materials with differing signal loss configurations to ensure the most accurate representation of the venue they are modeling. So for this reason, we’ve made adding new materials to the database easy for our customers to do themselves. The materials database (and the components database) is fully editable for our customers to add their own materials and allows them enter information such as: transmission loss per band, conductivity per band, a material image (viewable in 3D) and then design properties such as trace color, texture width, height, etc.

Here is an example of one of my favorite materials: Water at 20^oC

**Water Material: Signal Loss by Band (2.4GHz shown)**

To read more about how to edit the components database, check out this blog.

Prediction Calibration

Unique to iBwave when it comes to network design software is the ability to calibrate prediction results with a live reading from the venue. So for example, when designing a Wi-Fi network and you have done an active or passive survey on the site, you can then use the measurement readings to calibrate the prediction. Because while you may have the right wall material selected in the model, you never know what is behind the wall that could impact the signal strength – metal beams, wood, etc. Using a live reading from the site to calibrate gets you that much closer to prediction accuracy. In iBwave Wi-Fi and iBwave Design there is also a ‘Prediction versus Measured Data’ report that can statistically show you the results of prediction versus the live measurement.

Here is a screenshot of prediction calibration, as well as the ‘Prediction versus Measured Data Report’. In these two reports you will see that the mean error, absolute mean error, and the standard deviation prior to calibration are all significantly higher than after we ran calibration using the passive survey measurements.

**Prediction Versus Measured Data Report (No Calibration)**

**Prediction Versus Measured Data Report (With Calibration)**

Incline Surfaces

I covered this topic fairly thoroughly in a blog post a couple of weeks ago, but it’s an important factor when it comes to prediction accuracy so I am also including it here. The ability to accurately model incline surfaces for venues which have inclined surfaces (I’m thinking stadiums, shopping malls, airports, subway tunnels, etc) can be invaluable for ensuring the network prediction during the design phase is a realistic representation of how the network will perform post-installation. In the one case study I did using a subway station/tunnel as an example, the difference between using incline surfaces during modeling and not can lead to a prediction difference of about 35dBm – which in reality translated to the users of the network having good signal strength, or none at all.

Here are the screenshots from the subway station example.

**Flat Model with No Incline Surfaces (showing a good signal strength)**

**With Incline Surfaces (showing in reality how the network will perform poorly)**

What are some other factors you have noticed have a large impact on accurate prediction results?

Wirelessly yours,

Kelly

Modeling with Incline Surfaces vs. Modeling Without: What’s the Impact?

One of the key benefits that set us apart from cellular & Wi-Fi network planning and design software is the ability to model incline surfaces. But why is this such a benefit? In this blog, I take a look at the value of being able to model incline surfaces by diving into a mini-case study of a subway tunnel Wi-Fi network design showing the prediction results of a subway station using just a flat model, versus the prediction of the same subway using a model with incline surfaces. In it, you will see what a difference incline surfaces can make—both in performance and in cost.

The Flat Model Approach

In the following model of the subway station, the modeling has been done with no incline – everything is modeled flat. The area we will focus on to see the difference will be the area circled red in the image, which is the staircase that leads up from the subway platform to the main level of the station.

Now let’s look at that same flat staircase area after running the signal strength heat map to see what the simulated Wi-Fi signal strength is:

Expected Signal Strength for the staircase area is mostly around -65 dBm – pretty decent.

So in this case, when the designer looks at the predicted performance of the network they could conclude that the network meets network performance expectations and the design is complete. And when the customer reviews the design with the prediction, they will see performance should meet their set KPI’s and sign off on the design.

But let’s take a look at what happens when this same subway station and staircase area is modeled accurately to real life with an incline surface.

The Same Venue with Inclined Surfaces

As can see in the below heat map, when you accurately model the staircase with an incline surface, a real difference in network performance prediction results. In fact, a difference of about 35 dBm.

Expected Signal Strength for the incline staircase area is mostly around -100 dBm (pretty bad).

As you can imagine, the troubleshooting and re-design work that will result from having such a difference in the simulated network performance and the go-live network performance will be significant. So let’s look at a few of the ways this performance difference will now impact you and the project.

How does not using incline surfaces put you at risk?

Performance
Costs
Customer Trust

Performance

From looking at the prediction results in the subway station example, this one is pretty obvious. There is a very clear difference in performance when you design with a flat model versus an incline model. In this case, there was a difference of about 35 dBm for signal strength. Which means when the design done using the flat model is installed in the real subway tunnel where incline surfaces exist, there will be a serious performance issue once the network ‘goes live’. Which brings me to my next point – the increase in costs that can result when a venue does not include correctly modeled incline surfaces.

Costs

Where there is poor performance post-installation, there is troubleshooting—and where there is troubleshooting, there can be large costs associated with it. Fact is, when an installed network does not perform as predicted during the design, significant costs can result. Costs to troubleshoot the issues, costs to re-visit the site, costs to re-design the network, and then costs to implement the required changes to the network. It also costs in terms of time—the fewer issues there are to troubleshoot post-installation, the less time you will spend on that design and the quicker you can move onto the next. The quicker you can move on, the quicker you can grow your pipeline and revenues.

Customer Trust

And last but certainly not least, there can be an impact on customer trust when a network does not perform as was presented to them during the design and approval stages of the project. For venue owners, the more troubleshooting, additional site visits, additional time spent testing and re-designing, all translates to inconvenience for their customers and costs for them.

iBwave Venue Model Examples with Incline Surfaces

And now, just for fun, I include a short video to show off some of the impressive 3D models done in iBwave that take advantage of incline surfaces

What has been your experience in using iBwave to design incline surfaces? Do you notice a difference?

Wirelessly yours,

Kelly