Why Did Pivotal Develop WaveScape?
By Brett Mills, Product Manager, Pivotal Commware
Pivotal developed the first three members of its mmWave product ecosystem – Echo 5G indoor subscriber repeater, Pivot 5G outdoor network repeater, and Intelligent Beam Management System (IBMS) for network management and optimization – because nothing like them existed.
Pivotal developed the fourth member of its ecosystem — WaveScape — after determining that existing RF tools were inadequate. While the current set of network modeling tools utilized by carriers do an excellent job of using statistical models to predict lower-frequency mobile networks, they fall short modeling more deterministic and line-of-sight-based mmWave frequencies.
So, Pivotal built its own tool from scratch to leverage the unique physics of mmWave. WaveScape ingests the highest-resolution GIS data available to perform accurate line-of-sight calculations and ray-tracing to qualify individual residential units for fixed wireless access. Where other network modeling tools typically use 10-foot resolution GIS data, WaveScape can model resolutions as high as 10 centimeters, which allows for significantly more accurate coverage predictions in millimeter-wave frequencies.
This precision allows carriers to guarantee a higher SLA and reduce hidden operational costs associated with missed predictions, including service calls, cancelled subscriptions, and troubleshooting. Furthermore, the WaveScape optimizer allows carriers to account for the CAPEX costs of each piece of network equipment, and it allows them to compare and optimize the incremental cost vs. incremental coverage of each piece of network equipment. As an example, the tool can identify situations where additional gNodeBs are required vs. when significantly less-expensive repeaters like Pivot can achieve similar outcomes. WaveScape also serves as a platform that allows carriers to precisely target their mmWave coverage. By overlaying the highest-available resolution population, demographic, and internet connectivity data, the tool can provide guidance on how to bring mmWave coverage to the places that need it the most.
Beyond providing guidance and optimization for existing networks, WaveScape can perform analysis on new markets with no existing mmWave coverage. By ingesting candidate locations of gNodeBs as well as sites that can host Pivot like utility poles, lamp posts, and private building corners that a carrier may have access to, the tool recommends placement and orientation of new network elements to reach a given target coverage level. Furthermore, the tool can dynamically ingest and reoptimize based on updated real estate requirements, new target metrics and newly deployed equipment. Recommendations are driven on a cost-per-incremental coverage basis and the tool allows users to update and refine their costing models.
In summary, mmWave can deliver on capacity-intensive and low-latency applications that subscribers expect from 5G. Limited line-of-sight (LOS) conditions and propagation challenges associated with mmWave dictate denser networks than ever before and significant planning is required to balance densification with responsible CAPEX. Legacy macro-cell planning tools are not up to the task of modeling small-cell deployments and many of the fundamental assumptions break down when simulating mmWave. To fully unlock the potential of this, spectrum carriers need an accurate and scalable modeling tool like WaveScape that is built natively on the physics of mmWave.