Why Optimize End to End V1.0

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Why Optimize End-to-End?

Customer Case Study

Issue 1.0 – January 12 th 2011



End-to-End Case Study:

• Value Delivered:

• Reduced CAPEX & OPEX• Improved Network Quality

• Why Optimize End-to-End?

• Optimization Case Study Details:• Objectives• Network Challenges• Solution Approach

• Root Cause Analysis• Impact Summary• Results – Before & After• Conclusion

Agenda



• Tangible Financial Value:

• $10M CAPEX Savings• $1.5M / Annum OPEX Savings

• Better End-to-End Network Quality:• 10% Improvement in Accessibility

= Call Blocking

• 10% Improvement in Retainability= Dropped Calls

Value Delivered



KPI Metrics and Business Impacts

Parameter / KPI Improvement

Inter-MSC HO 40%

HO Success Rate 5%

Paging Success Rate 2%

C7 Signaling Bytes 20%

Inter-SGSN RAU 30%

MSC/SGSN Capacity 10%

SDCCH Blocking 0.20%

SDCCH Drop Rate 0.10%

TCH Blocking 0.50%

TCH Drop Rate 0.10%

IRAT Success Rate 2%

KPI BasedRevenue

Improvement

Reduced CAPEX&OPEX Spend

Less TouchingNetwork & Rework

15%Improvement

10%

Improvement

25%Improvement



• With increasing use of Mobile Devices and Applications,Networks are experiencing unprecedented Capacity Demands.

• Mobile Operators must change their Business Models to ensurethat they drive profits from the Mobile Internet and are undertremendous pressure to Cut Costs

• To keep costs lean while maximizing Network Capacity andQuality of Service, it is critical to Optimize the Network from End-to-End

• Cerion is the world leader in Mobile Broadband NetworkOptimization. Our solutions reduce Network Costs, ImproveNetwork Performance and balance the tradeoffs betweenNetwork Capacity, Cost and Quality of Service.

Why Optimize End-to-End?



Case Study – Details

Ericsson GSM Network – 17 MSC, 35 BSC, 40,000 TRX



Objectives

• Deliver End-to-End Optimized Network Design

• Improve End-to-End Network KPI’s• Increase Network Capacity

• Improve Network Quality

• Increase Handover Success Rate

• Reduce TCH and SDCCH Blocking

• Increase Paging Success Rate

• Reduce SDCCH/TCH Drops

• Deliver an Engineering Process that improves NetworkPerformance and Quality on an ongoing basis



Network Challenges

Daily CPU BH

• Core & RAN

Performance Issues

• Core & RAN CapacityIssues

• Reactive CapacityPlanning Process

• Massive Growth – 10K Site adds/Month

Excessive MSC Load

Imbalanced MSC Load

Imbalanced Radio Control Load



End-to-End Solution

CS, PS, Subs

& TransactionForecasting

PolygonPlanning

Re-ParentingPlans

Capacity

Demands&

Requirements

Leverage Cerion Optimiser™

To Deliver A Fully Integrated Predictive Planning Process

CSVRImplementation(Sequence Re-parenting)

Implementation(Sequence Re-parenting)

Measurement

&Assessment

(Actual Performance)

Measurement

&Assessment

(Actual Performance)

Network

Design(What-If Scenarios)

Network

Design(What-If Scenarios)

DESIGN

MSCSGSN

BTS

Node B

CS/MGW

BSC

RNC

Capacity

Planning(Predictive Capacity &

Demand Modeling)

Capacity

Planning(Predictive Capacity &

Demand Modeling)

IMPLEMENTPLAN

OPERATE

FORECAST

UnifiedNetwork

Model



Cerion Optimiser™ – System View

CerionIntelligenceBuilder™

E2E Capacity Planning

KPI Performance Optimization

Server & Border Optimization

Site-Level Engineering

10

Implementation Planning

Accurate GrowthModeling

Network

Measurements



• Non Optimized Core Borders• 7000 Inter-MSC Handovers

generated by by non-optimizedborder.

• Non-Optimized RAN Capacity• Poor Borders with high

imbalance in utilization

• Non Optimized Cell Capacity• Traffic and Signalling Congestion

Optimiser™ Root Cause Analysis

Cell T RX SDC CH SDCCH Blocking SDCC H Drop

8513 4 2 69 2

8514 4 2 82 3

8516 4 2 26 2



Before:• Non Contiguous Serving Areas• Elevated Signalling Levels• Core Processing Exhaust• Excessive Inter-Office Trunk

Requirements

MSC Impacts

MSCO

MSCI

MSCE

MSCF

MSCN

MSCQ

MSCA

MSCB

MSCG

MSCC

MSCH

MSCP

MSCK

MSCL

MSCJ

MSCD

MSCQ

MSCI

MSCE

MSCF

MSCN

MSCQMSCA

MSC

B

MSCG

MSCC

MSCH

MSCP

MSCR

MSC14

MSCJ

MSCD

After:• Optimized Serving Areas

• Reduced Signalling levels• More Processing Capacity• Lower Inter-Office Trunk

Requirements



Before:

• High imbalance in utilization with service

blocking• Increase in complex signallingtransactions

• Limited knowledge about target sites forhandoff gives performance issues

Radio Controller Impacts

After:

• Improved balance with increased network headroom

• Less network signalling and lowerprocessor loading

• Improved Accessibility, Retainability andhand-off performance,



Benchmarked

Performance Gains



MSC Handover Reduction

BEFORE:BSC2 was island between 3 MSC’s

MSCEMSCD

MSCB

MSCA

AFTER:Reduced Inter MSC Handovers 40%

MSCEMSCD

MSCB

MSCA

BSC2

BSC2

40% Reduction In MSC Handovers



MSC Capacity Improvement

Page 1

Before

After

984K

12000K

Holiday Weekend

MSC ACapacity Improvement

MSC BCapacity Improvement

15% Improvement In MSC Capacity



Handover Success Improvement

MSC AHandover Success

Improvement

MSC BHandover Success

Improvement

6% Improvement In Handover Success

Reward

No Reward

Reward

No Reward



SDCCH Drop Rate Improvement

Before

AfterSD Drop= 0.55% SD Drop= 0.45%

Improvement atBorder Cells

10% Improvement In SDCCH Drop Rate



KPI Performance Improvement

Penalty

NoPenalty

Reward

Penalty

NoPenalty

Reward

10% KPI ImprovementMoved Related Payments From Penalty to Reward Zone



Conclusions

• Delivered End-to-End Optimized Network Design

• 15% Reduction in CAPEX & OPEX

• Improved End-to-End Network KPI’s

• 10% Quality Improvement in Accessibility & Retainability

• Increased Handover Success Rate

• Reduced TCH and SDCCH Blocking• Increased Paging Success Rate

• Reduced SDCCH/TCH Drops

• Provided an Engineering Process that improved NetworkPerformance and Quality on an ongoing basis

End-to-End Optimization Improves Your Competitive Edge

Documents

Why Optimize End to End V1.0