Nokia AVA Geo Performance Analytics

Nokia of America Corporation ұсынады

Geo Performance Analytics: Follow the customers and Identify where and why network issues happen

It is becoming increasingly important to have the proper measurements sources and solution in order to have a clear understanding of the network behavior, traffic distribution and keep under control the actual network status. Drive testing have been used for many years as one of the fundamental sources for performance monitoring and analysis. Identify areas with high UL packet loss, retransmission rate and BLER impacting the user experience and Reducing drive test costs for network performances analysis is always the major concern raised by Customers across the Globe.

To solve these challenges, Nokia has developed an innovative approach covering different requirements for the type of analysis and the specific geographical area of interest

Nokia’s solution is based on proper processing of 3GPPP MDT data for 4G. Using this network feature, the L3 and L2 data are enriched with the location (Lat & Long) of the users provided by the GPS of the UE. Thanks to this approach it is possible to generate different KPIs maps (e.g. RSRP, RSRQ, Payload, Failures, Handover etc) with high location accuracy helping to identify the issues, the causes and drive properly the network optimization activities.

Nokia’s Geo Performance Analytics service provides very detailed and accurate KPIs maps describing how the network is used, where are the critical performances located, and drives the radio optimization and capacity expansion activities.

All this applied without sending people in field and with the desired frequency of refreshing the data maps and using Big Data platform as MS Azure which is capable to handle billions of records.

The main advantages of this service and approach are:

- to handle big file size & huge processing power of L3/L2 call logs with Minimization of Drive Test (MDT) features activated

- to identify and display with high accuracy(<10m) density of events and measurements from the UEs

- to show the maps overlayers to facilitate the cross correlation of events and measurements and identify easily the reasons of poor performances and corrective actions.

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