When it comes to 5G network planning, it’s all too easy to get caught up in the complexity of it. The new 5G technologies like massive MIMO and beamforming, the new high-frequency mmWave spectrum, and the diverse, environments demanding connectivity; they all compound the challenge. AI-driven RF planning can and does alleviate much of this complexity. But to realize the full benefits of accurate 5G planning, even the best algorithms still require best-in-class 3D geodata designed and validated specifically for RF planning.
In a previous blog, we looked at the 5 key requirements for effectively planning and optimizing your 5G RAN. One of these pillars – or perhaps more of a cornerstone – is the data upon which your 5G RF plan is developed. Accurate 3D geodata means you can model your 5G network with confidence.
Why 3D geodata matters in 5G RF planning
In many cities, 70-80% of mobile broadband traffic comes from indoor locations. This means the subscribers are not necessarily at ground level, making traditional 2D planning ineffective. To deliver the quality of service your customers expect in complex dense urban environments, you need to be able to successfully plan how your network takes advantage of the latest 5G technologies.
The adoption of mmWave frequencies for 5G services has made this even more acute. The high frequencies of mmWave spectrum can support massive bandwidths for eMBB use cases and high-capacity sites – but the tiny wavelengths of these frequencies suffer a lot of attenuation from obstacles. It could be the high-rise office block or apartments, or something as seemingly innocuous as trees coming into leaf – they can and will all have a measurable impact on not just the performance of your network, but also your ability to maximize the profitability of it.
For fixed wireless access (FWA) use cases, where a stable connection between the customer premises equipment (CPE) and the cell site is vital, being able to accurately predict where you can provide FWA services is critical to your success.
High-resolution 3D map data ensures you can accurately predict your 5G network coverage in complex environments and deliver the quality of service your customers expect.
Case study: how 2D mapping left an operator missing out on $67 million from its 5G FWA service
Take this real-world example of an operator selling 5G fixed wireless access to residential and business customers. Their sales team did a great job of selling FWA contracts to customers, as they rolled out new cell sites and expanded their coverage. However, there was a problem. They were selling contracts based on 2D mapping and where they expected coverage to be.
Customer complaints and the cost of insufficient coverage
The result was that instead of customers celebrating their ultrafast home broadband, the operator saw customer complaints increase. The cost of dispatching engineers to try and remedy the situation by mounting CPEs on rooftop poles added to both capital and operating costs.
Their business case for 5G FWA was in danger of being holed below the water line.
The business impact: Threats to the 5G FWA business case
The business challenge they faced was as real as it was serious. They calculated that using their existing high-resolution 2D mapping data, 15% of all properties “covered” by their FWA service in fact had insufficient coverage. The option (after the customers had complained) was either a full refund for their service or a repositioning of the FWA CPE on their property. The cost of this, they calculated, was worth about $1,000 for every single customer that was miss-sold – the equivalent of over $34,000 per site.
Lost opportunities: Revenue impact of misclassified coverage areas
But it’s not just about the cost of customer complaints. They realized they were also missing out on significant opportunities. With an incorrect ’insufficient coverage’ categorization for 17% of properties using their 2D data, they were losing revenue by not even trying to sell FWA to customers who had perfect coverage. With an ARPU/profit per user per month of $20, this rolled up to be worth nearly $21,000 in lost revenue per site over the coming three years.
The consequences: Sub-optimal cell locations and revenue loss
Inaccurate 2D geodata mapping of their FWA services meant they were not only siting cells in sub-optimal locations, they were also failing to effectively monetize the 5G FWA services once the network was deployed.
The business case for 3D geodata mapping
The business case for 3D geodata mapping became a straightforward question of math.
The cost-benefit analysis of 3D geodata mapping
Nationwide, the operator calculated the total cost/benefit meant they were missing out on over $67 million on their bottom line.
Enhancing RF planning with best-in-class 3D geodata
To address this would require an investment in best-in-class 3D geodata, designed and validated specifically for RF planning. This would give them visibility into the heights of buildings and their roof structure, the canopy height of groups of trees and how they compare to the height of buildings they surround, and it would even allow them to model the canopies and trunks of individual trees.
The ROI of 3D geodata: Recovering lost revenue
By purchasing 3D geodata to both reduce costs incurred by targeting customers with insufficient coverage and maximize revenue by targeting all customers with sufficient coverage, the operator calculated they could realize $67 million in lost revenue – and an ROI over 1,360% for the 3D geodata.
How Infovista combines high-res digital maps and advanced AI modeling to deliver the most accurate 5G planning
To accurately model your wireless network requires modern geodata sets that are designed and validated specifically for RF planning. Infovista’s premium Geodata provides high-resolution (1-2m) digital maps with 3D building and vegetation polygons, designed specifically for RF planning. This is critical for accurate planning of 5G in dense urban areas, especially at mmWave frequencies and in FWA cases as seen above. For areas where lower resolution data is acceptable, Geodata provides a 2.5D medium resolution (5-10m) solution, ideal for suburban areas, and a 2D low resolution (20m+) solution for nationwide and large coverage footprints.
Integrated with Planet’s AI-powered propagation modeling
Skylines, our next-generation 3D mapping data for accurate 5G planning, is integrated with our AI-driven Planet RF Planning and optimization solution. This gives you end-to-end support from a single vendor, propagation model compatibility and calibration, and a full plug-and-play format and delivery structure. The innovative 3D geodata has been developed with 5G in mind and is validated with key network equipment vendors, ensuring your network plans are fit-for-purpose in the environments you are deploying.
R&D innovation for 5G: Combining Geodata with AI
The characteristics of 5G spectrum and technologies create new complexities for modeling the network, particularly when it comes to understanding attenuation detail. Accurate integration of vegetation means you can model trees with more accuracy, by considering trunk and canopy height when calculating propagation loses. This is particularly significant for the accurate prediction of picocell and small cell coverage in situations where these cells and users are both below the canopy. By integrating the Geodata with AIM, Planet’s AI-powered 3D propagation model, you can also simulate when trees are in-leaf and out-of-leaf, allowing you to analyze coverage through the seasons.
How to retain your customers loyalty: A personal anecdote
Here’s a personal analogy. I remember years ago moving into a new house and getting satellite TV. It was Autumn, and we loved being able to watch the US boxsets. And then Spring came. And then Summer came. The tall trees in the neighbor’s garden created some lovely cooling shade, but also ruined our TV signal. Frustrated, we called the cable provider from whom we’d received so much marketing through the letterbox, only to find they, in fact, couldn’t connect our property. Even more frustrated, we moved to the fiber broadband provider and got our on-demand TV through them. 10 years and a house move later, we’re still with that same operator.
So, what’s the point behind this analogy? If you want to keep your customers and acquire new ones, you need an accurate understanding of where they are, the environment around them and the experience they are likely to get. And it all starts with the network planning.
