Advanced Network Optimization Techniques Utilize 3D Geodata
Shortly after the first RF planning tool was developed, ray tracing models were created to simulate dense urban environments.
In the early days, computation from ray tracing models was slow and 3D geodata – when available – was expensive.
The primary use case was network design, but like any simulation, the quality of the 3D geodata dictated how transferable the knowledge gained was to the real world.
For areas outside of urban cores, an acceptable level of mobile network coverage and performance simulation accuracy was achieved in rural and suburban environments
utilizing 2D geodata including terrain, clutter, population and road information.
In 2012, 3D geodata and more evolved “urban models” are widely used on a daily basis by engineers all over the world. But with a paradigm shift in availability and cost of 3D geodata,
radio network simulations without 3D maps in dense urban and urban morphologies are often inaccurate.
Similarly, according to ComputaMaps partner and mobile design and optimization experts, MobileAllies, current performance of geolocation methods based on network geometry and
observed time delays from multiple transmitters are also highly inaccurate in dense urban environments.
They offer very limited indoor performance capabilities and are location-error prone due to signal multipath propagation and bad network geometry.
MobileAllies has cooperated closely with ComputaMaps, to prove what is possible on high accuracy geodata.
The company takes network design and localized optimization services to a new level, using accurate radio signal calculations based on 3D maps,
real network traffic and network measurement-based localized system performance.
Average performance localization accuracy
Network grid based
*depends on network cell size
Network design is more effective when methods are based on live network performance and traffic load.
MobileAllies use sophisticated and customized network performance localization methods to represent GSM, UMTS and LTE system behavior in a 3D space. Network aspects such as: traffic,
(S)HO events, call drop events, system access events, system noise, cell dominance and others are localized outdoor and indoor with accuracy under 50 meters.
To achieve the best possible localized performance accuracy, MobileAllies depends on network hardware and technology, customized hybrid geolocation methods and multiple sources of system performance
data including system-specific internal and external tracing, system performance counters, drive and walk test, etc.
MobileAllies has demonstrated that existing and future network performance including network coverage, accessibility,
retainability and capacity can be maximized using planning processes with 3D maps from ComputaMaps as the foundation.
RF planning and optimization is evolving to deliver improved performance optimization for urban environments.
For more information about MobileAllies and their proprietary approach to improving network performance utilizing ComputaMaps 3D geodata, please visit