Tilting Dalam Optimasi

7/29/2019 Tilting Dalam Optimasi

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Ultima Mentor Power and Tilt

www.schema.com



Agenda

Optimization data sources

Data Modeling for pilot power and antenna tilt

optimization Optimization algorithm overview

Optimization Definitions:

2

Goal configuration

Constraints and Locks

Budget

Viewing optimization progress

Reports and Layers

Provisioning and validation



Power and Tilt Optimization Objectives

Improve network coverage and quality by

improving the mobiles RSCP and Ec/Io

Improve network capacity by balancing traffic

3



Power Optimization Algorithm

Mentor predicts how power changes affect the model:

Pilot power changes influence:

EcIo of each pilot

Pilots in active set

Service area (traffic distribution)

,

can be forecasted more accurately by the model

Once the optimization can forecast the network behavior for

every possible solution, the Genetic Algorithm finds the optimal

solution

4



Optimization Overview

Optimizer and Evaluator Inter-relationship:

Optimizer – responsible for suggesting different network

configurations based on Genetic Algorithms

Evaluator – Evaluates each suggested network

configuration and grades it according to the sub-goal

configuration

Optimizer Evaluator

sub-goal

grades

configurationchanges

GA



Optimization Input Data Sources

Hardware configuration data (Antenna locations,

heights, tilt, azimuth, antenna profiles)

Network switch dumps: Network elementconfiguration (e.g., pilot and control channel power

configuration, handoff algorithm parameters,

Mobile measurements and call detailed

information (IOS Traces or GPEH files)

Network Statistics Data – KPIs based on counters,Power and Traffic Statistics

6



Optimization Overview

Genetic Algorithm proposes evolving sets of Power and Tilt changes

Each proposed change is translated to changes in RSCP for all

modeled geo-located mobiles

Each such change is evaluated using a What-If Simulator that

evaluates the predicted network status after the proposed

The predicted network status is given a fitness score function (“how

good is the network in the sub-goals eyes”), which is optimized

The algorithm ends when optimization stabilizes (typically 5000 -

50000 evaluations)

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Pilot Power & Antenna Config. Change Impact

Pilot Power changes result in RSCP changes changing the powereach mobile receives

Antenna configuration changes result in changes in antenna gainsin different directions, changing the power each mobile receives

These gain changes are translated to changes in sector carrier

Pilot Power change: When increasing/decreasing pilot power by 1dB all mobiles experience the same gain/loss (1dB). (Nogeographical modeling needed – geo-locationing is not needed)

Antenna Configuration change: When changing an antenna by 1degree tilt each mobile experiences a different gain or lossaccording to its position relative to the antenna. (Geographical

modeling is needed - geo-locationing is needed)8



Power and Tilt Optimization Wizard

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Optimization Wizard Stages

Select sectors to optimize

Select carriers

Select/Filter Model Dates to use

Configure optimization goals such as Coverage,

Quality, Capacity. Goals are statistical, optimizingselected cluster’s performance

Select parameters to optimize and their constraints

Set Budget

Run Optimization

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Selection Set and Calculation Set

The Selection Set sectors are considered to be

changed by the optimization engine

The Calculation Set is used to define the effectingand effected sectors for power and antenna

optimizations

The Calculation Set is a NL based first tier of theSelection Set

A model for power and antenna optimizations

should be based on a network with a good NLconfiguration

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Optimization Goal is composed of sub-goals

Sub-goals are divided into 2 categories

Mobile sub-goals (Improve RSCP, Improve Ec/Io) Sector Carrier sub-goals (Reduce Power Usage, Reduce

OVSF Code Usage)

Optimization Goals

The Optimizer maximizes a fitness functioncomposed of all sub-goals defined by the user

Coverage and Quality: RSCP and Ec/Io

Capacity: RSCP, Ec/Io, Power Usage, OVSF Code Usage

Customized: User defined sub-set

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Optimization Goals (Contd.)

Balance between sub-goals is automatically

calculated

Sub-Goals are converted to a continuous fitness

function

Fitness improvement is calculated relative to current

network status Fitness improvement is calculated on an area which

includes the selection set and all sectors that can be

affected by the changes

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Optimization Progress Graph – Fitnesses

14



Optimization Progress Table – Qualities

15



Constraints Window

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Optimization - Locks and Constraints

Environment problems which prevent cells from

being optimized:

Inactive sector – Sector is indicated as inactive

Missing data – Some information is missing for the sector

In-building antenna – Sector is defined as in-building

Multi-antenna sector carrier optimization is notsupported – sector carrier has more than one transmitting

antenna



-

(cont.)

User locks (in Schema Format or Sector Properties):

Do not optimize power – sector carrier locked for power

Do not optimize electrical tilt – locked for e-tilt

Do not optimize mechanical tilt – locked for m-tilt

Do not optimize beam width – locked for beam width

Do not optimize azimuth – locked azimuth Definitions on cell level and constraints file



Optimization - Locks and Constraints (cont .)

User constraints

Limiting constraints – constraints given in Wizard and/or

Schema Format are too tight

Current values do not comply to constraints – current

value violates Wizard and/or Schema Format constraints

power per sector – applicable only if “same power” optionis checked

Profile Issues

No unique profiles in antenna model – e-tilt, beam width

combination is not unique

Constant electrical tilt – This model has only one profile or

all profiles have the same e-tilt

–



Optimization - Locks and Constraints (cont.)

Statistical issues (missing logs and/or KPI’s):

Low message count – sparse logs

Low message duration – sparse logs

No traffic statistics – missing traffic KPI’s

– ’

Low traffic reliability – inconsistency between traffic from

KPI’s and from logs

Low interaction rate – much of the traffic is 1-way Surrounded by sector carriers with low statistics – this

sector carrier is neighbored by another sector carrier with

statistical locks



Budget

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Budget (cont.)

If “Limit budget” is checked, solutions that exceed

the budget limit are ruled out by the GA. Otherwise

cost is calculated only for informational purposes

Power changes are not considered at all

Access to site is considered once for each site which

is changed in any way Mechanical changes are simply summed up

Electrical changes are considered once for each site

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Optimization Progress Window

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Power Optimization Reports

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Four different reports:

Summary

Constraints Analysis

Carrier selection set statistics (Before vs. After)

Carrier calculation set statistics (Before vs. After)



Power Optimization Changes

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Power Optimization Layer

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Power Provisioning and Validation

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Creating xml configurationfile for the updating of CPICH Power settings

Validating CPICH Power implementation examiningnew configuration files



Summary

In this session we…

Became familiar with Mentor’s power and tilt

optimization data sources and algorithm

Reviewed the different sub-goals needed in order to

perform power and tilt optimization

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Reviewed Constraints, Locks and Budgetconsiderations

Reviewed Mentor layers and reports

Reviewed Mentor’s provisioning and validationfeatures

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