ultima mentor - engineers daily operation - automatic analysis and optimization.pdf

7/28/2019 Ultima Mentor - Engineers Daily operation - Automatic Analysis and Optimization.pdf

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Gur Lavie, Director Product Marketing

Ultima MentorEngineers Daily OperationAutomatic Diagnostic, Resolution and Optimization

Voice & HSPA


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IMPORTANT NOTE

This is NOT a MENTOR product presentation

For a detailed explanation of the Mentor Product architectureand components, please see the relevant PRODUCT

presentation

ALL the features which are described in this presentation are

part of the standard package

ALL of Mentor capabilities are based on data automatically

collected from the network.

MENTOR does NOT USE predictions and drive tests data

MENTOR is a Multi-Vendor tool supporting all relevant

vendors

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Engineering Activities (1)

With Mentor You can automatically Identify and resolve

Coverage Holes

Areas with poor network quality

Pilot polluters

Pilot dominance problems

Low downlink and uplink throughput

Over-shooter (killer sectors)

Cross-feeders/swap cells *version 7.2

Resolve all of the above with

Power, Parameters & Tilt Automatic Optimizations

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Engineering Activities (3)

With Mentor You can automatically Identify and resolve

VIP customers high drop rate

Specific IMSI/IMEI trouble Ticket

Equipment Types problems (uplink/downlink)

Roamers coverage and quality

Analyze each drop location, cause, events

Resolve all of the above with

All Automatic Optimization Features

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6

Examples of Mentor Usage by Engineers

Problem Identification

Coverage, Quality, Capacity, Throughput Voice & HS Data service

Individual subscribers problems

Automatic Problem Resolution OneClick Neighbor List plan and provisioning

IRAT automatic planning

Automatic resolving of SC conflicts

Automatic Tilt changes recommendations

CQI, RAB and other parameters optimization


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Analyze KPIs in GIS and Table

Quality, Capacity, Throughput & Backhaule KPIs

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KPI Layer Example

8

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How do I Know I am improving the network

Analyze the network from statistical perspective

Includes

Message statistics

EcIo/RSCP distribution

Pilot Dominance

Cells statistics

Traffic load

Power distribution

Soft HO factor

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Types of GeoMaps in Mentor

Traffic

Minutes of use

Erlang

Users

Performance

Best server

RSCP,EcIo Soft/softer HO factor

Pilot pollution,Pilot dominance

Uplink/Downlink Throughput/volume

UeTx power

Drop map, IRAT, mobile drop

Arc Maps

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Where do I need to improve coverage/quality/throughput ?

Show the coverage quality for top dropping cells

Define a regular Ec/Io map Define Ec/Io as the map

Set filtering parameter to KPI and condition to top%

Show theproblematiccoverage quality areas for top dropping cells

Define a regular Ec/Io map Define Ec/Io as the map

Set filtering parameter to KPI and condition to top%

AND filtering MAP for Ec/Io bottom 5%

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Identifying Problems with GeoMaps

Use Layer->Show Combined Selection Set on Map to see which cells are

selected for the specified condition

Use the threshold slider to dynamically modify thresholds

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Automatically Fixing Neighbor List Problems

Visualizing Neighbor Lists

Changing Priorities

Adding and removing Neighbors

Unique Neighbor List Quality Indicator

Automatic Provisioning Script to implement changes

14Neighbor List Before Neighbor ListAfter


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Case B - Neighbor List Optimization

Before optimizationAfter optimizationSurrounding cluster, needs

further improvements

Handover rate change

indicates the potential to

improve the current Neighbor

list.

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IRAT analysis and optimization

Pinpoint IRAT events location

Identify 3G and 2G serving and receiving cells

Automatically fix the IRAT Neighbor List

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Automatic Resolving Scrambling Code Conflicts

Existing sites co-SC solution

user initiated as recommended by the Neighbor

List reports

New sites

Scrambling Code planning

Neighbor List planning

Redraw

Global SC solution

SC carving (For Femtocells etc)

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Improving Coverage/Quality/Throughput by Antenna Parameter change

Power, Tilt, Azimuth & Beam Width Optimization Wizard

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Optimization Sample

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Example of Antenna Parameter Optimization

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EcIo Crossing threshold

Resulting changes after optimization

Optimization Automatically

Executed in the server

0.01.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

-18

-17

-16

-15

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-13

-12

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-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0

Best Server EcIo [dB]

[%o

fmessages]

Ec/Io [dB] - Before

Ec/Io [dB] - After

l h


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Case C Quality Improvement with Mentor

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Case C Capacity Improvement with Mentor

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Power Efficiency

increase

25 %

A l i d i i i A A S i


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Analyzing and optimizing DATA Services

APN (Access Point Names) analysis in Mentor

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Case A Improving HSDPA User Throughput BH (Kbps)

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Case A Improving HSDPA Cell Throughput BH (Kbps)

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xxx330182037504

xxx330213260708

xxx330214227492

xxx330117989235

xxx330206751371

xxx330206725429

Individual Subscribers Analysis


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Subscribers drops correlated with EcIo, RSCP & KPIs

Subscribers Problems

T d l ifi i


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Top droppers classifications

bl h l b b bl


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Trouble shooting Individual Subscriber Problem

l i


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Count of Drops Country125663 United States of America

29 Canada

13 United Kingdom

7 Mexico

5 France

3 Cyprus

2 Brazil2 Spain

2 Austria

2 Singapore

2 Netherlands

1 Australia

1 Argentine Republic

1 Norway

1 Sweden

1 Italy

1 Kuwait

1 Germany

Top Voice dropping IMSIs Roamers

Count of drops Country

123657 United States of America

234 United Kingdom

59 Canada

49 France

10 Italy

7 Belgium3 Belgium

2 Hong Kong (PRC)

2 Mexico

2 Sweden

2 Indonesia

2 Germany

2 Spain

2 Japan

1 Switzerland

1 South Africa

1 New Zealand

1 Spain

Top HS dropping IMSIs Roamers

Roamers analysis


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Summary

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Summary Mentor Workflow Building Blocks


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Sample Workflow:

2G-3G

Inconsist.

IRAT

Optim.

Summary - Mentor Workflow Building Blocks

Neighbors

Coverage Capacity

Parameters Customer

Analysis

Quality

Antenna

Parameters

Optimization

Objectives

Analysis

SC

Optim.

Over-

Shooting

Power

Optim.

Electrical

Tilt

RAB

Power

CQI

Optim.

Mech.

Tilt

NL

Optim.

CEM GeoMaps KPIs

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Data

Product Differentiators


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Product Differentiators

RNC/MSC based licensing: no per-seat limitations

Distributed-Centralized automatic data collection and modeling Most Accurate Geo-positioning engine, including moving, stationary,

in-building and outdoor subscribers

Automatic Neighbor List and SC optimization

Automatically generated full cluster plan not just tables of data

CO-SC problem identification and automatic resolution IRAT optimization

Advanced parameter usage: overshooting sectors,

symmetry/reciprocity enforcement, locking and more

Automatic power, tilt, and parameter optimization

Advance data processing

GPEH, UETR, CTR, RBS

Encapsulated RF knowledge instead of overwhelming engineers

with more data

SmartCluster optimization

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[email protected]

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ultima mentor - engineers daily operation - automatic analysis and optimization.pdf

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