HEAVY.AI announced HeavyRF, an extension of the company's deep analytics platform that uses NVIDIA Omniverse to create digital twins that help telco network operators speed deployments of wireless networks. The industry's first radio frequency (RF) digital twin solution, HeavyRF enables telcos to simulate potential city-scale deployments as a faster, more efficient way of optimizing cellular-tower and base-station placements for best coverage. With NVIDIA Omniverse, HeavyRF is instantly compatible with a large set of complementary tools for reality capture, as well as advanced antenna and network tools leveraging machine learning.
These can be used to design networks even in complexly dynamic environments such as ports and to simulate software-defined networks down to the packet level. HeavyRF allows telcos to minimize site-deployment costs while maximizing quality of service for both entire populations as well as targeted demographic and behavioral profiles. The module supports network planning and coverage mapping at unprecedented speed and scale.
This can be used to rapidly develop and evaluate strategic rollout options, including thousands of microcells and non-traditional antennas. Simulations can be run against full-resolution, physically precise LiDAR and clutter data interactively at metro regional scale, which avoids down sampling needs and false service qualifications.