Statistical Method for Measuring Mobile Network Energy ... · Statistical Method for Measuring Mobile Network Energy Consumption Dave Bossmin Researcher, Energy Efficiency Standardization

Statistical Method for MeasuringMobile Network Energy Consumption

Dave BossminResearcher, Energy Efficiency StandardizationEricsson

04 June 2015

Statistical Methods for Determining Mobile Network Energy Efficiency | Public | © Ericsson AB 2015 | 2015-06-04 | Page 2

› Reasons for Measuring Mobile Network Energy

Consumption

› Challenges with Measuring Large Items Such as Mobile

Networks

› Approaches Taken By Other Industries When Measuring

Large Items

› Explanation of the Statistical Method

Presentation OutlineMeasuring Mobile Network EE


Why Measure Mobile Network Energy Consumption?

Network Measurements Bring Network Understanding

› Primarily for Technical Reasons

– Many Energy-Saving Features Activated At Network Level

– Lab Measurements of Components In Isolation From Network Misses

Impact of these Features (e.g., Macro Cell Sleep)

– Extrapolations of Network Values from Lab Measurements are

Unrepresentative

› Benefits to Both Operators and Vendors

– Operators Gain Understanding and Ability to Improve the Energy

Consumption of their Networks

– Vendors Use Live Network Conditions to Demonstrate and Improve

Energy-Saving Features


Mobile Network MeasurementsNo Small Feat

5500 km

3500 km

13,000 Sites

* Canadian Cell Tower Locations2

Not The Typical “Box-In-The-Lab” Measurement Problem!

* Canadian Cell Tower Site Count1

300 km


Mobile Network MeasurementsProblem Statement

› Need to Measure Something Big

› Want to Limit to Expense and

Effort of Making the Measurement

› Need to Understand the Accuracy

of the Measurement


Mobile Network Measurements:Measure Every Site

Expensive

Accurate

Measured Site* Canadian Cell Tower Locations2


”From a survey of 1400 residents, 34% of respondents

support the government’s initiative.

This population estimate is accurate

within +/- 3.1%, 19 times out of 20.”

Cues from Other Industries:Measuring “Big Things”

Polling Industry Statement:

A Sample Size of Thousands Estimates a Population of Millions;

Significant Reduction in Measurement Effort


Guidance From Other Industries:Polling Industry

› Don’t “Measure” Every Person

– Doing So is Cost-Prohibitive

› Measure Small, Random Sample

› Sample Used to Estimate Entire

Population

› Statistical Analysis Used to

Determine Accuracy of the

Population Estimate

Apply Same Approach to

Mobile Network Energy Consumption Measurements


Statistical Method:Mobile Network Energy Consumption

› Network is a Population of

Base Station Sites

› Choose Random Sample of

Sites from Population

› Measure Average Energy

Consumption of the Sample

› Use Average to Estimate

Network Energy

ConsumptionMeasured Site


1. How Do We Know That Our Sample is Representative of

What Is Happening in the Overall Network?

2. How Do We Choose the Size of our Sample?

3. What Happens to Future Measurements as the Network

Grows and Changes?

Questions Regarding the Random Sample Approach


Meaning of “Representative Sample”

› Site Energy Consumption Has Many Influences

– Population Density, Climate, Traffic Load, Equipment Configuration

› Each Influence Is Distributed Differently Across Network

– Population Example: 60% Urban, 40% Rural

– Climate Example: 80% Warm, 20% Cool

Population Density3 Climate4Mobile Network

Random Sample Considers All Influences Simultaneously


XXXX----3333ssss XXXX----2222ssss XXXX----1111ssss XXXX XXXX++++1111ssss XXXX++++2222ssss XXXX++++3333ssss

› Sampled Energy Consumptions Have a Statistical Distribution

How Representative is the Sample?

χχχχ

ssss

Sample Mean

StandardDeviation

��

�Margin of

Error

› Total Energy Consumption Estimate

› Accuracy of Estimate

True MeanSample Mean

Statistical Analysis Will Indicate Sample Representativeness


Significance of theMargin of Error

Accuracy of the Energy Consumption Estimate is Known

› Satisfies Key Requirement of the Measurement

– Accuracy of Population Estimate

– Difference Between Sample and Population Distributions

› Eliminates Need To Manipulate Random Sample

– Avoids Introducing Bias into Sample

– Removes Guesswork From Overlapping Distributions

› End-User Has Much Control Over This Value

– Influenced By Sample Size “n”

– Diminishing Returns With Increasing “n”

±��

�

ssss


› Decide on Desired Level of Accuracy in the Estimate

– Margin of Error and Confidence Level (+/- 3%, 19 times out of 20)

› Develop First-Order Estimate of Population Statistics

– Population Mean (µ) and Population Standard Deviation (σ)

– Identify Major Site Configurations in Network

– Understand Energy Consumption Influences (e.g., climate, traffic load)

Determining Sample Size “n”

�� ∗=±

2�

� ∙

› Requires “Back-of-the-Envelope” Calculation Exercise

– Based on Margin of Error Definition for Entire Population

* Formula for 95% Confidence Level


› If Measurement Equipment is Permanently Deployed

– Option 1: Network Grows Around Measurement Equipment

› Future Upgrades Can’t Be Based on Sites Being Measured

› Risk of Systemic Error

– Option 2: Randomly Add Measurement Equipment Each Year

› Full Direct Measurements Eventually Achieved

› Margin of Error Used in the Interim

› If Measurement Equipment is Temporarily Deployed

– New Sites Randomly Selected With Each New Measurement

› Note that Polling Firms Don’t Call Same People Each Time

Dealing with Growth and Changes to the Network


Summary: Statistical Method

› Measuring Network Energy Consumption

– Mobile Network is a Population of Base Station Sites

– Random Selection Considers All Site Energy Consumption Influences

Simultaneously

› Statistical Method Limits Expense and Effort

– Measuring Less Sites Significantly Eases Measurement Burden

› Statistical Method Provides Necessary Accuracy Statement

– Defined by Margin of Error

– Based on Spread of Energy Consumption and Size of Sample

– Operator Has Full Control Over Accuracy/Cost Trade-offs


1. Government of Canada (Industry Canada), Facts About Towers

– http://www.ic.gc.ca/eic/site/ic-gc.nsf/eng/07422.html

2. Canadian Cellular Towers Map

– http://www.ertyu.org/steven_nikkel/cancellsites.html

3. Government of Canada (Statistics Canada): Population Density By Dissemination

Area in Canada (2006)

– http://www.statcan.gc.ca/pub/91-003-x/2007001/figures/4129885-eng.htm

4. Government of Canada (Environment Canada): Surface Air Temperature

Climatology: Observations of June-July-August from period 1963-1993

– http://members.shaw.ca/driebergens/sports/cycling/images/summtemp.png

References

Documents

Statistical Method for Measuring Mobile Network Energy ... · Statistical Method for Measuring Mobile Network Energy Consumption Dave Bossmin Researcher, Energy Efficiency Standardization