Self Organizing Network

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Communication Service Providers (CSPs) always strive to provide the best user experience to their customers while trying to keep CAPEX & OPEX expenditures down. Specifically, the fast evolution of wireless networks caused parallel operations in 2G, 3G, 4G, and 5G. On top of that, the number of parameters that must be set in the network elements drastically increased and left no remedies for communication service providers but to maintain these manually. The necessity for AI and Automation driven Self Organizing Network (SON) came up right at this point. The Innovile Self Organizing Network Platform (SON), ready to meet this necessity, can empower communication service providers with its cutting-edge technology to improve network performance for the best orchestration. The Platform is designed to assist communication service providers improve network service and performance rapidly with flexible, automated, and end-to-end network optimization solutions. The Innovile SON fully supports network transformation and helps operators run next-generation networks (5G).

  • Provides comprehensive SON dashboard.

    • Active Modules per vendor, location, and node
    • Detailed SON action info
    • Parameter and policy comparisons between node and locations
    • Site DB inconsistencies, OSS access issues
  • Enables full set rollback scenarios

  • User defined module integration

  • Available for 2G-3G-4G and 5G RAN network optimization

  • Improved algorithms with ML and crowdsourcing data

  • Reduces CAPEX and OPEX

  • Increased capacity growth by 20%

  • Decreased drop call by 18%

  • Increased throughput by 15%

  • Increased energy saving by 4%


The multi-vendor and multi-technology SON Platform automatically and dynamically optimizes the all-network elements until the optimal configuration is achieved for the best performance. Communication service providers can automatically detect and fix network problems before they affect the customer experience. Thereby, SON Platform increases Quality of Service (QoS) and reduces churn. With real-time visibility into network status, traffic statistics, and parameter changes, CSPs maximize network coverage, boost capacity, and improve network KPIs. All in all, it is quite right to say “simplifying the complex has never been this much easy before Innovile SON.”


Automatic Neighbor Relation

The Automated ANR module coordinates the operations of adding and removing neighbors. Time and frequency configurable ANR use Configuration Management, Site Plan, Performance Management, Trace and Location Based Geodata for adding neighborhoods to the network. The user-friendly interface quickly defines constraints for neighbors and easily exports Neighbor Revision Scripts and/or Complimentary Scripts. The execution of scripts can either be offline or online automatically.

Configuration Consistency Audit and Correction (CAC)

CAC pinpoints the inconsistencies in the network. For each vendor/technology, parameter/MO values that violate the policy are detected and corrected by the module. The main task of the module is to automatically correct errors and turn network configuration into an integral form. External cell definitions, blind handover definitions, LAC, TAC compliance, BCCH group filling, duplicate neighbors, and objects are checked daily and adjusted by default.

Capacity and Coverage Optimization (CCO)

The module is developed to search and indicate Over or Undershoot cells, make congestion analysis, and detect cross feeder cells for their best performance in their planned areas. CCO can be done automatically or manually. In the automatic mode, CCO adjusts the tilt angles of the cells or the strength according to specified parameters of CSP’s KPIs. The manual mode, on the other hand, generates a list of recommendations to engineers which indicates specific steps to correct in order to achieve the best cell and network performance.

Mobility Robustness Optimization

MRO optimizes the Cell-to-Cell handover, Idle mode, and Cell-Reselection parameters to improve the quality of communication and minimizes the Call Drop rate, HO failure rate, standby problems, and influence of interference.

Self-Healing (SH)

The SH module constantly monitors the network to detect performance degradations and fixes them. The Module uses PM and Fault Management (FM) data to detect cell outage and/or sleeping cells and takes necessary actions to revert the network back to its optimal performance by sending reset command automatically.

Dynamic Load Balancing (DLB)

Traffic is distributed evenly according to the operator’s network strategy, and the module utilizes the PM data based on the values of the cell / carrier utilization percentage, idle values, offset values, DL power changes and inter-RAT selection parameters every half hour. For each change, the KPI values of the next period are compared with the previous period to check the impact of the changes. If the impact is positive, changes are done automatically, and if not, roll-back plan is activated. The module helps to distribute traffic to less congested neighborhoods.

Automatic Plug-and-Play Optimization (APO)

APO automatically aligns new sites to their new location with best neighbors, codes, and parameter templates.

Code Optimization (CO)

CO module calculates interference calculation algorithms and assigns them to on-air cells to change the parameters of BCCH/BSIC, PSC, PCI, and RSI.

Energy Saving (ES)

The module aims to minimize the power consumption of base stations without causing any user experience degradation. Based on historic data of the prediction and capacity analysis, ES turns off cells/carriers.

Special Event Management (SEM)

SEM is designed to orchestrate the parameters of local zones during a mass increase in traffic, such as soccer derby, Olympiads, etc. Similar with DLB, SEM uses short term PM data directly from cells and performs changes by 2 minutes intervals. The Module helps to quickly distribute the peak loads by taking necessary actions on time.

User Centric Optimization (UCO)

UCO can make the necessary analysis as subscriber based or cell based, can visualize the experience of a user or a group of users in terms of accessibility, persistence and quality of radio network connections and can perform special tasks to improve the communication quality (voice and data) for user-defined operators or subscriber groups as well.