The new solution, to be demonstrated at MWC this week, is designed to help enterprises including mobile network operators (MNOs) save both time and money when performing 5G radio frequency planning. The companies estimate that it would enable enterprises to reduce the time to identify real estate acquisition for 5G small cells as well as cut the cost of RF design by more than 40%.
The solution is a unique blend of technologies. It embeds machine learning software and a service delivery framework from Infosys; expertise in RF and C-RAN (cloud radio access network) design from Shields; and large, precise, scalable 3D datasets derived from terrestrial LiDAR and other remote sensed content from HERE.
The expertise of HERE in extracting features and 3D derivative objects such as poles, trees, terrain models, and buildings lends a new level of precision to RF planning for 5G mmWave networks that far surpasses the accuracy of conventional GIS data.
That means greater efficiency in the mmWave RF planning process. More accurate network planning takes the guesswork out of transmitter selection and placement. It also enables MNOs to cut costs by significantly reducing the number and length of physical site-surveys. With network design tasks taking just a few days, MNOs can more quickly perform upgrades, install new equipment, add capacity or respond to environmental changes.