3G Workshop May 2005 - Richard Edge.ppt

Slide 1 New Concepts for Optimization Enhanced Approaches Using Measured Data presenter Richard Edge Contents Developing a new concept Veritune Validating the Veritune concept Developing a practical s[.]

New Concepts for Optimization

Enhanced Approaches Using Measured Data

presenter Richard Edge

Developing a new concept

The importance of antenna optimization in

UMTS

If a cell causes too much interference in a UMTS / WCDMA network…

… frequency planning is no longer an option…

…the only options are power and antenna optimisation.

Antenna optimisation in UMTS is both more frequent and important than in GSM networks

Downtilt, azimuth and power

changes control are used to

control radio propagation

Changes identified by:

Validation drive 01 Optimized!

How do we speed up the process?

KPI analysis

Antenna changes

in field

Field drive

Identify changes to antenna coverage

Validation drive 01 Drive Test

Reducing the loops is key

to reducing time to revenue:

 Get an acceptable solution

as early as possible.

How do we improve the

certainty that our changes

will work?

Time consuming

Relatively quick

Some principles for a new concept in

optimisation to reduce the number of loops

Improve prediction accuracy by simplifying

the problem (rather than increasing the

complexity of the model)

Wherever possible use real data (rather

than predicting measurable information)

Guide the user towards the solution (rather

than prescribing a solution automatically)

Present results in the same format as

measured data (rather than presenting a grid

of data)

(Picture – NASA Space Pen)

Review – how a planning tool predicts network performance

Interfering Cells

Interference Generation

Required inputs: Map database, model diffraction/penetration/ reflection assumptions, antenna performance and configuration, traffic geographical distribution, building penetration, interferer link budget, traffic modelling, power control, RRM modelling, mobile location in

buildings.

Path Loss

Required inputs: Map database, model diffraction/penetration/

The planning tool prediction process

Pilot RSCP

Served Users RSSI

Pathloss Prediction

Service EbNo

Applying the principles - Veritune

Interfering Cells

Interference Generation

Required Inputs: Map database, antenna performance and

configuration of changed interfering cells.

The Veritune prediction process

KPI analysis Field drive

Actix Veritune

on desktop

Validation drive 01 Optimized!

time

Optimisation loops are

taken out of the field onto

the desktop

An improved antenna optimisation process with Veritune

Antenna changes

in field

Less cycles saves time, reduces cost

Traditional process

With Actix Veritune

Validating the Veritune concept

Validation approach

Before

After Drive

• Validation was carried out using historically collected data

• Synthetic drives calculated off ‘before’ measured drives were compared to ‘after’ measured drives, and the error at each data bin calculated

Input measurements

Trials of 4 clusters (33 sector changes, 20 control sectors) have been carried out across a variety of rural, suburban and urban environments, in flat and hilly terrain

A total of 8545 data bins were considered, approximately 427km driving

No data filtering was carried out:

 Sector heights ranged between 12m and 48m

 Measurements both within and beyond the main lobe by

bearing were considered

 All ranges were considered up to 14km (including less than 500m)

The validation results

Standard deviations significantly improve upon typical

propagation model accuracies (benchmark 8dB – top of the below

4.8dB without 2 outlying sectors

How consistent are the results?

Distribution of error with distance

Error Plot with Distance

Developing a practical solution

Implementing the principles in practice

2

Enabling 3 easy steps to fast, in-office optimization:

Step 1 Identify poorly performing areas

Step 2 Review guidance towards possible solution Step 3 Simulate the effect of antenna changes

Identify poorly performing areas

Review guidance towards possible solution

 Trace and identify

Retain local knowledge

input for informed

decision-making

2

Simulate the effects of antenna changes

the difference on the

map and in statistics

and see cumulative

effects

queries and reports to

be run on the synthetic

log file

View effect of changes

3

Summary

The value to an operator

Reduce drive testing

 How much would you save by a 20% reduction in required drive tests?

Accelerate time to revenue

 How are your business targets helped by reducing the number

of optimisation iterations by 15%?

Reduce antenna changes

 What would be the benefits of 20% less antenna re-work?

Improve engineers efficiency

 How much more effective could engineers be with a single tool for acceptance and tuning?

Thank you

Richard Edge

richard.edge@actix.com

+44 7971 409514