ariesoACP
- unleashing the power of customer centric automatic planning
Would you like to base your network planning on real customer call information?
ariesoACP enables you to take a holistic view of cell planning and optimization - increasing network quality, mitigating the adverse impact of high data usage from new data phones and, above all, positioning new infrastructure to maximise ROI.
Combining intelligent simulation and optimization algorithms, ariesoACP delivers a world leading automatic planning technology, efficiently searching the all possible configurations to deliver the optimum network design. Flexible configuration enables consideration of your unique design criteria, allowing the trade-off of maximum network capacity, the least number of dropped calls, minimum capital expenditure or the best coverage for customers.
ariesoACP is the world's first ACP that can be used exclusively with geo-located customer call data - ariesoACP does not require data from drive testing nor pathloss predictions, instead optimizing against real network traffic data and measured pathloss from ariesoGEO installations. Integrated with ariesoGEO enterprise solution, ariesoACP offers the powerful capability of basing network in-fill, operational optimization and 4G/LTE deployment planning on subscriber call data. Gone are the days of trial and error adjusting power output and altering mast tilt based on limited drive test data or inaccurate predictions - integrating geo-located call data with automatic cell planning optimizes the network based upon the real breakdown of in-building and off-road calls.
For applications where geo-located data is not available, ariesoACP is compatible with all industry leading planning tools. Powerful multi-layer analysis allows the consideration of network sharing, network merge and new technology overlay across GSM, CDMA, UMTS and LTE technologies.
Benefits seen by operators include significant increases in the efficiency of network engineers, as well as gaining 20% better return on investment within the network.

