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Jan 18 2016

Field insights: Optimal indoor cell placement

Finding ideal locations for indoor small cell placement raises crucial questions.

  • Where’s the greatest user traffic in each enterprise building?
  • What’s the best cell placement, per floor, to avoid interference from the macro?
  • How will indoor cells affect wireless performance outdoors?
  • How much will a solution cost?

State-of-the-art indoor 3D modeling helps service providers get faster, more accurate answers to these questions. It quickly quantifies the issues so service providers can understand their options before physical placement begins.

This level of insight delivers 2 important benefits:

  1. Optimal indoor cell placement can be streamlined.
  2. Service providers have better information for identifying the best solution to meet their needs. They can even develop cost-effective priorities for how to deploy small cells over time.

Here’s how this indoor small cell placement process works.

3-dimensional views, quicker results

Indoor 3D modeling simulates the conditions that each small cell will experience in a specific location. To do so, it goes beyond 2D representations, which are often based solely on information from a building’s ground level. Instead, 3D simulation considers multiple buildings, multiple floors in each building, and the height of any building sitting between an outdoor cell and the indoor floor being studied.

Adding the 3rd dimension is important, because signal propagation varies greatly between the ground floors and top floors of a building.

The analysis starts by identifying problem areas. Then modeling capabilities are focused on addressing those key issues. For coverage problems, the next step is to identify all the buildings where coverage is poor on one or more floors. For capacity issues or throughput constraints on the macro network, indoor 3D modeling identifies where to place small cells for offloading the macro — and simultaneously increasing throughput for users.

The optimal placement of each cell is calculated automatically — and the results of each placement can be forecast. These results include how much traffic will be carried by each cell, its macro offload or its throughput. And the cost of potential indoor solutions can be projected, too, to support business decisions in the planning phase.

More accurate heat maps

To get the best results from an indoor small cell solution, service providers need to develop a clear picture of user traffic. That includes identifying where wireless customers use devices on each floor of a building — and where they’re using the most data.

These traffic “heat maps” are most accurate when they’re generated from multiple data sources. That’s because some data sources may be better for identifying user locations, while others offer greater insight into data usage. Nokia, for example, uses a combination of the following techniques to gain a more complete view of wireless usage, with finer granularity:

  • Per-call measurement data heat map — Based on geolocated network trace data, this heat map is a good predictor of wireless data volume within a specified location. (Nokia multi-vendor capabilities with its 3-D GeoLocator tool will deliver geolocation information.)
  • Social media heat map — Drawing on aggregated social media data from commonly used sources, this type of heat map is a good source for fine-tuning an understanding of user location.
  • Demographic database traffic heat map, if needed — If other sources are lacking, this data can quantify the number of employees in a building to help identify potential traffic hotspots. Information about the type of business, number of businesses, and number of employees in each business is especially helpful when buildings are poorly covered and don’t register in call trace data.

Optimal indoor cell placement calculated automatically

In this next phase, advanced indoor 3D modeling determines where small cells are needed, because macro coverage is insufficient. To do so, it automatically analyzes the heat maps that have been developed and looks for floors with low to medium macro coverage and high user densities.

Then it identifies macro signal strength and quality, floor by floor. And it calculates where macro rays can’t penetrate or are reflected by nearby buildings. To facilitate accurate prediction, Nokia uses a state-of-the-art 3D ray tracing model for this part of the analysis, which flags macro database inconsistencies.

Finally, 3D modeling automatically establishes optimal placement for each indoor cell — all across the intended site. So service providers can take a proactive look at their options for improving indoor coverage and performance. And once small cell solution choices have been made, physical deployment can be faster and easier.

Indoor small cell placement results quantified

To learn the results of specific indoor small cell placements, 3D modeling runs a combined outdoor-indoor simulation, in which all the small cells and the macro cell are operating in the recommended configuration. Based on what a service provider needs to determine, the findings can measure:

  • The amount of traffic carried by each small cell
  • The number of small cells needed to cover the target floors
  • The amount of traffic served per building
  • Offload provided to the nearest macro sector
  • Improvements to end-user throughput

Traffic offload is important to network health. So service providers often want to proactively identify potential offload from a single building — or from a cluster of buildings.

For example, in midtown Manhattan, an Nokia indoor design and modeling tool was used to project traffic offload from a set of congested buildings. The findings predicted offload of 44% by deploying indoor solutions in 13 buildings within a 5 macro cluster — which would then improve throughput for indoor users by more than 1000%. And outdoor users would also see a throughput gain of 69%, as a result of offloading the indoor users.

These measurements are valuable for quantifying the benefits of a specific indoor solution. So service providers have the insight they need to set deployment priorities — and create step-by-step plans for improving coverage and capacity. To support these plans even further, 3D modeling can estimate the equipment and service costs for each step in deployment.

Modeling expertise and advanced tools

Nokia offers unique indoor 3D modeling and costing capabilities. We have the only platform that can model indoor and outdoor environments simultaneously. We can create heat maps from multiple sources. And we can help service providers identify ideal locations for offloading a particular macro sector quickly. In addition, these capabilities are supported by end-to-end network expertise and RF knowledge.

RELATED MATERIAL

In-building solutions web page

Other “Field insights” blogs:

Small cell network optimizationDeploying enterprise small cellsSmall cells in large enterprisesSmall cells retain enterprise customers

Our authors look forward to your questions and comments.

About Jean S. Jones
Jean was a member of the team responsible for marketing Alcatel-Lucent’s industry leading wireless services and enterprise small cell portfolio, and now continues in a global services marketing role with Nokia. She has over 20 years of expertise in product, services, solutions and vertical marketing. Jean joined Lucent Technologies in 2002 and was responsible for product marketing of Lucent’s IP data networking portfolio and partnerships. She has held several marketing positions across the wireline and wireless business groups. Jean directed the team that brought 2 strategic wireless solutions to market for Alcatel-Lucent: META for mobile backhaul and End-to-End LTE. Prior to joining Alcatel-Lucent, she was Director of Product Marketing for Tenor Networks, a top-funded start-up in Massachusetts. Jean also served as Senior Marketing Manager at Bay Networks/Wellfleet, an industry pioneer of IP routing, later acquired by Nortel Networks where she helped drive some of the first IP-VPN managed service deployments with major service providers. Jean holds an MBA from Babson College, located in Wellesley, Massachusetts.