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Mobile Network optimization

SpeedChecker has partnered with Univo5G to offer complete end-to-end solution for MNOs looking to win no.1 positions in their target markets.
Identify improvements at a glance; fine tune deployment and reduce CAPEX by 10 to 30%.

Mobile network optimization

Combining data from all available sources such as crowdsourced vendors and OSS systems and making all sense out of it to extract value is no easy task. SpeedChecker has partnered with Univo5G, leading experts in capacity planning and network optimization,  to offer complete end-to-end solution for MNOs looking to win no.1 positions in their target markets.



continuous improvement cycle


Benchmark: QoE competitor benchmarking

Compare QoE across all your competitors and areas to identify areas where you need to improve.


Collect: OSS data of low performance sites

Retrieve 1 month of OSS data from low performance sites and compute subscriber's throughput by sector and time.


Analyse: Root Cause Analysis

Detailed analysis of the OSS counters and calculated voice and data model.


Correct: Apply correction

Operator uses analysis results to deploy only to anticipated needs, there is revenue increase because congestion is anticipated and treated before it occurs, with a reduction of customer complaints and churn.


Identify where to improve QoS at a glance

Automatic computation of the blocking probability at each node, with the ability to forecast the required investments and costs in order to, for example, increase the QoE of all subscribers from 1Mbps to 10Mbps.Calculations of the subscriber throughputs (also valid for FWA), by sector, during the Peak Hour, the second busy hour, ... anywhere within the cell, whether near the cell or at the cell edge. Results: QoE increase by an average of 19% resulting from monthly detection and treatment of degraded sectors, leading to a decrease in customer complaints and churn

LTE-4G network typical utilization

Fine tune deployment and optimize CAPEX

Make the most accurate voice and data forecast in the market, at the cell level (based on a unique probabilistic mathematical model as used in the nuclear industry). Engineers generally use trends at the BSC, RNC or regional level, but these forecasts are never correlated with investments since investments are made at site level. Results: deployments are phased only according to anticipated needs; there is a revenue increase because congestion is anticipated and treated before it occurs, with a reduction of customer complaints and churn.


Reduce CAPEX by 10 to 30%

Identify the exact dimensioning capacity of any node within a mobile network (2G, 3G and 4G) for a given blocking rate, depending on the traffic demand and its current configuration. Engineers usually increase capacity when they detect congestion, but are often unsure of the exact amount to be added. Results: decrease by an average 27% in capex of 2G, 3G and 4G master plans and massive reduction of OpEx (no need for additional up-dates because the level of node saturation and the amount of additional capacity needed was calculated more accurately)