Benchmark Analytics to Ensure Winner Position

Operator Challenge

The operator had invested notably to network quality & capacity, and expected to obtain the #1 position in the national network benchmark.  However an objective benchmark campaign proved the operator’s average DL speed was actually 3 Mbps behind the best network. This result was unexpected, as the operator had the most dense site-grid with the highest LTE-A capacity, and almost all performance KPIs looked favorable to the Operator

Omnitele Assignment

Quantify the reasons why there is gap to the other operator and provide an action plan for optimisation & expansions that will secure the winner position in the next benchmark campaign

Solution

Predictive analytics for drive-test measurement data, to quantify the true reasons behind the benchmark gaps and to provide concrete action plan to close the gap.

Input data to the analysis: Raw drive-test logs

Analysis

Step 1: Quantify cell-level root-causes’ net impact on the operator gaps

Operator 1 gets almost 4Mbps advantage from the lower LTE interference, and also smaller gains from better coverage, spectrum, MIMO. However, the disadvantage with lower modulation scheme alone turns the net difference into negative.

Step 2: Quantify cell level improvement potential from different actions

Achievable KPI improvement, and the resulting impact on the benchmark, is quantified for each sector. The action can include:

  • Coverage or dominance optimisation
  • Parameter optimisation
  • Spectrum expansions and new features

Step 3: Create the most feasible action plan to close the benchmark-gap

  • Network wide parameter-optimization
  • Radio optimisation in 7% of cells
  • Capacity expansions in 5% of sectors

Operator benefits from the project

Strategic benefits

  • Winner position secured for the next benchmark campaign
  • Concrete & prioritized action list to meet the targets
  • Optimisation campaign schedule cut from 5 months to 2 months

Quality benefits

  • +5 Mbps to average DL throughput
  • Maximum performance from the existing network assets

Opex savings

  • 45 % less OPEX in optimization to win the benchmark

Capex savings

  • 35% Capex saving in reaching the winner position

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