Energy Efficiency Measurements at the

Network Level

Sibel Tombaz

sibel@kth.se

KTH Royal Institute of Technology

Communication Systems Department

Anders Västberg, Mats Nilsson, Guowang Mio, Claes Beckman

Ki Won Sung, Jens Zander

1st ETSI TC EE Workshop 20-21 June 2012, Genoa Italy

Outline

� Why Energy Efficiency?

� Why We Need Network Level Measurement?

� Objectives

� Challenges

� Discussion

1. Key Performance Indicators (KPIs)

2. Network Level Measurement

3. Normalization Parameters

� Conclusion

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Why Energy Efficiency?

� Currently, 3 % of the world-wide energy is consumed by ICT

� Which causes about 2% of the world-wide CO2 emissions.

� Comparable to airplanes

� 1/4 CO2 emissions by cars

� Mobile broadband data usage has experienced dramatic growth.dramatic growth.

� 1000×more capacity will be needed in 2020!

� As a result, power consumption of mobile networks increases ××××2 every 5 years

� Energy prices also increase (expected: 3x in 7 years)

� Impose more and more challenging operational cost for

operators.

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Why EE Measurement?

� A EE measurement standard at the network level is required in order

1. To allow operators to monitor their energy figures

2. To be able to compare different networks.

3. To know the EE improvements from different solutions

• BS ON/OFF mode

• Smaller cells

• CoMP, etc.

4. To understand the EE levels of telecommunication sector (Environmental concern)

� A supporting model is also required in order

1. To understand the reality

2. To relate the results

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Objectives

� To propose a methodology which defines

� ”How to measure the energy efficiency of a given network?”

� ”How the gathered data will be modeled so that different networks which has completely different characteristics will be comparable? ”

� To be able to achieve these goals, we need to define

1. Key Performance Indicators(KPIs)1. Key Performance Indicators(KPIs)

• To make comparison

2. Methodology

• To indicate how to measure the energy efficiency

3. Model

• To represent the results and give insight about the possible improvement directions

4. Normalization Parameters

• To discard the impact of uncontrallable network parameters.

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Challenges

� Networks in nature have many unique properties that will affect the measured energy figures

� User profiles (3G% / 2G%)

� Amount of spectrum

� Coverage area (km2)

� Area Capacity (Mbps/km2)

� Climate

• Proposed methodology should not ignore these facts.• Interpret the results under the light of givencharacteristics.� Climate

� Environment (Rural% / Urban%)

� Etc..

� It is impossible discard the impact of all static properties on measured energy figures. Thus,

� We need to be careful while drawing a conclusion about the gathered data.

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characteristics.

Key Performance Indicators (KPI’s)

� What shall we use to indicate energy efficiency figures of mobile networks?

� In academia: ”Number of succesfully transmitted bits per joule”

� Amount of spectrum has a severe impact *

2log (1 )

tx

W SINRData Rate bitsEE

Power Consumption Joule aP b

+= = =

+

1500

2000

2500

3000

Are

a p

ow

er

consum

ption (

W/k

m2)

W=1.25 Mhz

W=3.5 Mhz

W=5 Mhz

W=10 Mhz

W=20 Mhz

� Amount of spectrum has a severe impact *

� Needs to be taken into account.

� KPI’s:

1. EE per bandwidth (bps/Watts/Hz)

� Positive impact of bandwidth should we removed with direct normalization.

2. Coverage per power (km2/Watts)

3. Number of users per power (Nusers/Watts)

*S. Tombaz, A. Västberg and J. Zander, Energy and Cost Efficient Ultra High Capacity Wireless Access", IEEE Wireless Communication Magazine, vol. 18, no. 5, pp. 18- 24, October 2011.

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0 5 10 15 20 25 30 35 40 45 500

500

1000

NBS

Are

a p

ow

er

consum

ption (

W/k

m

Key Performance Indicators (KPI’s)

� First of all we need to answer following questions:

1. How to define of number of users?

� #subscribers, #sim cards: Does not give the info how active is the user. (GSMA Approach)Approach)

� #active users: Does not give info if the user is satisfied or not.

� # satisfied users: It is very hard to define by operators.

2. How to define number of bits?

� Is it the total mobile traffic? (GSMA Approach)

� We should define some QoS requirement thresholds

3. How to find total power consumption?

� Based on electricity bill? : Black box approach!. (GSMA Approach)

� Direct measuring representative BS’s + scaling:

� Trade-off: Accuracy-Complexity!

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Network Level Measurement

� Constraint: Any other KPI’s in the network should not be affected by energy savings!� Shutting down some BS’s at low traffic load (network management) should not impact user

drop call rate.

� Thus, we need to define some network performance thresholds and check if the networks achieve the requirement during the measurement.

• This cant be achieved by looking to total amount of traffic!!! (GSMA Approach)

� Challenge:Challenge:

� How to define network performance?

• Minimum user data rate (It should also differ based on used service!)

• Drop call rate

• Latency

• Coverage (Availability)

• Etc.

� How to ensure QoS?

• Which will be different for different services.

• Which will change with time.

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Measured Traffic (e.g., during one week)

Network Level Measurement

� It can be problematic to introduce one QoS req threshold for each service?

� Data rate will be also important for video as latency, etc.

� We can introduce an utility function to represent the network performance by considering defined QoS thresholds!

� Gathered data can be used to calculate the defined KPI’s of the chosen network.

� This approach will prevent the unfairness of the comparison by giving credit to the network which satisfies the requirement!

� The network which

• has more coverage hole at night or

• has lower area capacity

� Challenge: We are aware that satisfying QoS does not ensure QoE.

� It is harder to define the relation between QoS and QoE.

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Will experience the direct impact in the calculated KPI’s

Normalization

� We can group the parameters that will affect the energy figures of the networks:

Dynamic parameters (Yi’s)•BS Deployment•Network Management Techniques ON/OFF, COMP (BS Operation)•EE of used equipments

(BS Power Consumption)

Static(Normalization) parameters(Xi’s)•Network Area•Spectrum•Environment (Urban, rural)•#Subscriber•Climate (Effect cooling PC)•Technology (2G/3G)

� To be able to make fair comparison between different networks, we need to discardthe impact of static parameters on calculated KPI’s via measurement methodology.

� Illustration:

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1 2 1 2( , ,...) ( , ,...)

measuredEE f Y Y g X X= +

max

theoretical

EE

refEE

Conclusion

� Energy efficiency represents an alarming bottleneck of the mobile radio networks.

1. Higher energy cost

2. Environmental concern

� Academia shows a great interest and propose different solutions to improve the figures.

� We also need a network level measurement methodology and a supporting model to

1. Know the EE gains by different solutions (which includes more than 1 BS)1. Know the EE gains by different solutions (which includes more than 1 BS)

2. Let the operators to monitor their energy figures periodically.

3. Compare different networks.

4. Analyze and relate the results to guide for improvement

� However, networks are unique and it is a big challenge to make a fair comparison between different networks. Therefore, to decrease the unfairness

1. Network performance should be defined based on QoS requirements to ensure that other KPI’s do not degrade as a trade for energy savings.

2. Most important static parameters should be defined and measured KPI’s should be normalized.

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