Planet Suite | RAN Planning and Optimization

Every stage of deploying and operating your 5G network is critical to its success. Infovista’s integrated 5G solutions allow you to plan, optimize and assure your 5G network. Our Planet, TEMS™ and Ativa™ solution suites provide unprecedented levels of accuracy and performance with the inclusion of a unique set of 3D, geolocation and automation capabilities, for every step of your network rollout and operations.

Our Artificial Intelligence Model (Planet AIM) greatly simplifies the way networks can be planned. It drastically reduces the operating costs related to calibration, while improving the reliability of wireless coverage predictions. With Planet AIM, engineers can execute wireless planning tasks much faster, delivering highly reliable network plans and ensuring their radio networks perform as intended. 

In many cities, 70-80% of mobile traffic comes from indoor locations. This means the subscribers are not necessarily at ground level. It is therefore critical to be able to plan your network in 3D. Planet natively supports 3D planning and optimization with support for high-resolution 3D geodata including building and vegetation vectors, 3D propagation models with ray-launching, 3D traffic maps, 3D beamforming analysis and 3D site selection.

Direct access to crowdsourced data in Planet provides an unprecedented level of geolocated insights into mobile subscribers' behavior and coverage experience directly inside your planning solution. By leveraging this valuable data when planning, your engineers can connect their designs with reality, improve the accuracy of their planning and optimization and ultimately, maximize the impact of your network investments. 

Planet offers seamless integration with iBwave’s world-leading in-building RF design solution. The integrated solution enables unification of indoor and surrounding outdoor network RF design activities. Users can automatically pull RF prediction data generated by Planet into iBwave Design for greater indoor prediction accuracy, as well as send indoor prediction information to Planet to greatly improve RF designs for campus environments.