Building the Networks of Tomorrow and Unlocking the full Potential of Mobile
The Evolution of Mobile Network Management
towards Self-Aware Networks
LTE-A Pro, 5G
2018 & Beyond
Generic software with a data feed configured by hand, used for performance monitoring.
Purpose-built software with a data feed configured by hand for reporting & correlated performance data visualization.
Open Loop SON
Purpose-built software with a configurable rules engine, automatic data fetching, and manual optimization actions.
Fully Automated Closed Loop SON
Automatically apply dynamic configuration changes based on a continual assessment of cell-level and network-level KPIs.
Automatically apply dynamic configuration changes based on KPIs assessment and geo-located traffic using subscriber data.
Virtual & AI Powered SON
Orchestration of virtual network functions, pre-planning dynamic configuration changes based on existing & future traffic predictions by using machine learning algorithms.
SON in Next Generation Networks
Next generation mobile networks promise a diverse range of services (transmission of a patient`s high quality diagnostic videos from a moving ambulance to a hospital for early triage and treatment, a Z-generation teenager watching a virtual-reality video to learn about dinosaurs). The differing connectivity requirements drives the need for flexible resource allocation as `network slices` in 5G. SON is critical to deliver these service level requirements with optimal network resource utilization, performance management and cost control.
AI Powered Network Management
If you experience muscle pain, dry cough, nasal congestion, then you may be suffering from a flu. Would you follow a prescription you get from a robot doctor when you input these symptoms? Or, what about identifying the problems even before they occur? Mobile network operators have passed the first stage by deploying a set of tools such as closed loop SON and real time performance management that evaluates the existing network conditions and implements automatic changes in the network. AI brings advanced capabilities to improve the network efficiency by speeding up the learning process from activities in the network. Self-Aware Networks based on machine learning techniques continuously tune the network for optimal performance and cost.
Automated Network Orchestration for better QoE and Improved Network Resource Utilization
Next generation networks will provide a transparent environment to measure and assess the Quality of Experience. Mobile operators need solutions that use these inputs to send commands to a Network Orchestrator ensuring overall QoE is improved. P.I. Works EVO Platform with Network Function Virtualization (NFV) functionality will provide additional flexibility for orchestrating the network resources. You can also capitalize on the benefits of NFV to dynamically scale the network to varying traffic demand by deploying and executing network functions and the resources required by these functions on demand.
Empower New Capabilities in the Cloud RAN
Today's mobile network providers all suffer from a common headache namely `site leasing`. There is a substantial growth in mobile network subscriptions together with increased pressure in finding extra physical space to mount traditional base station hardware. Virtualization of telecom centric equipment to commodity IT hardware in data centers will provide benefits and enable an alternative for capacity expansion for mobile operators. During this transformation, existing and new network planning, management and optimization capabilities have to be in the picture so that operators maintain the control over their network configuration especially in areas where non-virtualized RAN and virtualized RAN co-exist.
Defining the Future of Mobile Technologies
P.I. Works contributes actively to the European Telecommunications Standards Institute (ETSI), 3rd Generation Partnership Project (3GPP) standardization forum, and Global TDD initiative (GTI). We also work closely with operators, helping them drive evolution of mobile networks.