A coverage map is one of the critical assets used by wireless operators to provide a geospatial (or locational) representation of a wireless network service. It can take many forms in terms of depicting the actual service type, such as technology (like LTE or CDMA), device types, data rates, service quality and time. The last item, time, is an important one because it helps wireless operators understand today's coverage as well as future, potential coverage as they evaluate their network investments and future deployment plans.
RF engineers are the creators and key users of coverage maps, especially to measure progress on the implementations of their plans as well as to track objectives in terms of area, traffic and subscriber coverage. As technologies such as 4G/LTE evolve, new business models such as MVNOs are introduced and new subscriber devices appear in the market, these coverage maps will become increasingly necessary for decision making. Targets are defined by marketing, sales and other executives, and passed to the engineering team. This often helps to define and meet particular quality of service (QoS) targets and regulatory requirements that must be planned, understood, reviewed and checked, all based on the coverage maps.
There are three steps involved in coverage map generation:
- The first is integrating the data to prepare a simulation in a planning tool. This step is performed, as an example, with our Mentum Planet solution. Site configuration data is then entered into Mentum Planet, including network parameters from the live network. Data from other systems, such as site rollout data and other design inputs, may also be included.
- The second step is to generate maps in the planning tool, Mentum Planet. Many selections may be made during this step in terms of which cells/sectors, geodata section and other parameters to use to run the simulations. Predictive measurements are also required to organize the results into meaningful categories, such as 4G vs. 3G coverage or device support.
- Lastly, the service level statistics for each category are generated. For example, this could include projections of network traffic by QoS level in high churn markets.
The challenge for wireless operators today is that demand for this generation of coverage maps is drastically increasing due to a rapid influx of new approaches like small cells and new uses of the wireless network, such as smart meters and other M2M applications. This means that more people need to understand what is ‘covered' in the mobile network, and they need that information updated more frequently.
Stay tuned for additional posts in this series, where I'll speak further about the challenges of coverage map creation and some potential solutions.