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On the Design of Energy Efficient
Wireless Access Networks
Ph.D. Thesis Defense
Ph.D. Candidate: Sibel Tombaz
Advisor: Pro...
4 Conclusion
2 Thesis Focus & Research Questions
1 Motivation
3 Key Findings
Outline
Motivation
3
1000X mobile traffic
+ +
10-100X # of
connected
devices
10-100X
end user data rate
+
5X lower latency..
Affor...
Motivation
4
Today Future
 Mobile radio networks are responsible of
10-15% of ICT.
 15 nuclear plants.
 ICT is the 5th ...
Why to Save Energy?
5
• Energy constitutes up to 50 percent of
operators’ OPEX.
Energy efficiency=
OPEX efficiency
Lack of...
High Level Challenges
Equipment Level
6
BS equipment are optimized for full
load.
• Lack of load adaptation.
• Operate at ...
High Level Challenges
Node Level
7
In average BSs are not serving any users more
than 50% of the time during a year.
• Sti...
High Level Challenges
Network Level
8
Equipment Level
Node Level
Low utilization
Very low utilization
Network Level
• Depl...
4 Conclusion
2 Thesis Focus & Research Questions
1 Motivation
3 Key Findings
9
Thesis Focus & Research Questions
10
We focus on the network level problems with 3 main high-level questions:
1. How to as...
Literature Review & Research Gap
11
 Energy Efficiency Assessment
 Metrics: Various green metrics are proposed
to quanti...
Literature Review & Research Gap
12
 Energy Efficient Solutions
 Operational Solutions : Long-term sleep mechanisms aim ...
Overview of the Contributions
13
1. Energy Efficiency Assessment
- Metrics: Identify key aspects to be considered to avoid...
2 Thesis Focus & Research Questions
1 Motivation
3 Key Findings
4 Conclusion
14
Energy Efficiency Assessment
Metrics
15
 How to avoid misleading conclusions?
• Identify right indication of how to achie...
Energy Efficiency Assessment
Backhaul Power Consumption
16
 Backhaul solution: technology; topology.
 Mobile radio netwo...
Energy Efficiency Assessment
Backhaul Power Consumption
17
Urban Areas
 Macro+only densification
 Heterogenous deployme...
Energy Efficiency Assessment
Backhaul Power Consumption
18
Rural Areas
Macrocell deployment
Outdoor small cell deployme...
Energy Efficient Solutions
Architectural
19
0 5 10 15 20 25 30
0
500
1000
1500
2000
2500
NBS
AreaPowerConsumption(Watt/km2...
Energy Efficient Solutions
Architectural
20
 How much we can save through Hetnet solutions?
 Type of small BSs.
 Number...
Energy Efficient Solutions
Architectural
21
Scenario: Outdoor small cell deployment under
macro-cellular coverage.
 Unif...
Energy Efficient Solutions
Architectural
22
Scenario: Indoor small cell deployment
under macro-cellular coverage.
 Non-U...
Energy Efficient Solutions
Operational
23
 How much we can save through Cell DTX for a
given traffic pattern?
( )
24
0 0
...
5 10 15 20 25 30 35 40 45 50
0
500
1000
1500
2000
2500
Number of BSs
TotalCost[kEuro]
0 20 40 60
0
10
20
30
40
50
Energy C...
Analysis on Energy-Cost Tradeoff
Economic Viability Analysis
25
 Under which circumstances will an operator will get a to...
( )
11
(1 )
ref
N n n n
BS cnn
e E E
N
d −=
−
> ∆
+
∑
Analysis on Energy-Cost Tradeoff
Economic Viability Analysis
26
Exis...
Analysis on Energy-Cost Tradeoff
Economic Viability Analysis
27
Greenfield Deployment
 Solution: Energy efficient greenfi...
2 Thesis Focus & Research Questions
1 Motivation
3 Key Findings
4 Conclusion
Conclusions
29
1. How to assess the energy efficiency of a given network?
 Energy efficient does not always mean lower en...
30
Thank you for your attention.
Any questions?.... OR NOT?
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Ph d thesis_seminar_on the design of energy efficient wireless access_sibeltombaz

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"On the Design of Energy Efficient Wireless Access Networks"

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  1. 1. On the Design of Energy Efficient Wireless Access Networks Ph.D. Thesis Defense Ph.D. Candidate: Sibel Tombaz Advisor: Prof. Jens Zander Co-advisor: Dr. Ki Won Sung Opponent: Prof. Timothy O'Farrell Committee: Dr. Ylva Jading Prof. Di Yuan Prof. Mikael Johansson 23 May 2014
  2. 2. 4 Conclusion 2 Thesis Focus & Research Questions 1 Motivation 3 Key Findings Outline
  3. 3. Motivation 3 1000X mobile traffic + + 10-100X # of connected devices 10-100X end user data rate + 5X lower latency.. Affordable and Sustaniable
  4. 4. Motivation 4 Today Future  Mobile radio networks are responsible of 10-15% of ICT.  15 nuclear plants.  ICT is the 5th largest (3%) in electricity consumption.  Co2 emissions is comparable to the global aviation industry.  We are beginning of the new era.  Energy consumption of mobile networks increases ×2 every 5 years.  Unit energy cost: x3 in 7 years!
  5. 5. Why to Save Energy? 5 • Energy constitutes up to 50 percent of operators’ OPEX. Energy efficiency= OPEX efficiency Lack of Electricity Supply • Average temperature is increasing annually. • Government motivates CO2 reduction. Climate Change • Continuation of the global success of ICT needs to be enabled. Sustainable growth • Grid availability is challenging. • Delivering fuel to off-grid sites is costly.
  6. 6. High Level Challenges Equipment Level 6 BS equipment are optimized for full load. • Lack of load adaptation. • Operate at suboptimal points most of the time. • Technical drawbacks towards green wireless access networks. Energy waste!
  7. 7. High Level Challenges Node Level 7 In average BSs are not serving any users more than 50% of the time during a year. • Still consuming high idle power consumption • Technical drawbacks towards green wireless access networks. Energy waste! 0( )BS TRX p txP N P P= ∆ +
  8. 8. High Level Challenges Network Level 8 Equipment Level Node Level Low utilization Very low utilization Network Level • Deployment has been done for coverage and capacity; ready for the worst case. • Demand for high data rates limits the resource utilization. • Significant spatial variation. • 80% of the BSs carry only 20% of the traffic. • Almost constant power consumption. Energy waste! + +
  9. 9. 4 Conclusion 2 Thesis Focus & Research Questions 1 Motivation 3 Key Findings 9
  10. 10. Thesis Focus & Research Questions 10 We focus on the network level problems with 3 main high-level questions: 1. How to assess the energy efficiency of a given network? 2. How should wireless access networks be deployed and operated in an energy efficient manner? 3. What are the consequences of energy efficient solutions on total cost?
  11. 11. Literature Review & Research Gap 11  Energy Efficiency Assessment  Metrics: Various green metrics are proposed to quantify the energy efficiency.  Misuse of the metrics result in contradictory and debatable conclusions.  Models: Accurate power consumption models for BSs are proposed by EARTH.  The impact of mobile backhaul has been mostly ignored.  Energy Efficient Solutions  Architectural Solutions : Various homogeneous and Hetnet network deployment solutions are proposed to minimize the energy consumption.  However, contradictory conclusions exist:  densification, indoor small cell deployment.  Fairness has been overlooked.
  12. 12. Literature Review & Research Gap 12  Energy Efficient Solutions  Operational Solutions : Long-term sleep mechanisms aim to match the network capacity with the actual traffic demand have been widely investigated.  However, dynamic short-term solutions have been overlooked.  The coupling relationship between deployment and operation has been ignored.  Energy-Cost Tradeoff Analysis  Economic benefits has been limited to annual OPEX saving.  Energy Saving ≠ Total Cost Saving  Main sources of total cost and their relationship are missing.  There is no methodology for assessing the economic viability of any EE solution.
  13. 13. Overview of the Contributions 13 1. Energy Efficiency Assessment - Metrics: Identify key aspects to be considered to avoid misleading results. • How to get coherent results. - Models: We propose novel backhaul power consumption models and highlighted its importance. 2. Energy Efficient Solutions - Identify the main design parameters and their impact on energy efficiency. - Quantify the potential energy savings through clean-slate Hetnet solutions. - Develop a methodology to assess the achievable saving through fast traffic adaptive solutions (i.e., cell DTX). • Highlighted the benefit of holistic design (Deployment+Operation) 3. Energy-Cost Tradeoff Analysis - Introduce the total cost perspective. • Propose a high-level framework capturing the main cost elements. - Assess the economical impact of different solutions. • Viability analysis incorporating initial investment cost.
  14. 14. 2 Thesis Focus & Research Questions 1 Motivation 3 Key Findings 4 Conclusion 14
  15. 15. Energy Efficiency Assessment Metrics 15  How to avoid misleading conclusions? • Identify right indication of how to achieve green wireless networks. Bit per Joule Area Power Consumption max min totEE E≠  To prevent contradictory conclusions both coverage and capacity requirements should be taken into account.
  16. 16. Energy Efficiency Assessment Backhaul Power Consumption 16  Backhaul solution: technology; topology.  Mobile radio network deployment: homogenous, heterogeneous.  Deployment areas: urban, rural.  Expected traffic growth. 0 1 ( ) backhaul m tot i p tx i P N P P P = = ∆ + +∑ 0 1 ( ) m i i tot i p tx i P N P P = = ∆ +∑  Is backhaul becoming a bottleneck for green wireless access networks?
  17. 17. Energy Efficiency Assessment Backhaul Power Consumption 17 Urban Areas  Macro+only densification  Heterogenous deployment  Tradeoff between power saved by using smaller cells and idle power for backhaul.  Backhaul highly impacts the energy efficient solution.  Almost 50% is consumed for backhaul for dense deployment in 2020.  Switch power is dominant.  Fiber based solutions generally outperforms the other solutions.0 100 200 300 400 500 600 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 x 10 4 Area Throughput[Mbps/km2 ] AreaPowerConsumption[Watt/km2] HetNet deployment 2010 2012 2014 2016 2018 2020 2022 0 5 10 15 20 25 Year AreaPowerConsumption[KWatt/km2] With Backhaul Without Backhaul Hetnet Backhaul impact shifts the point where Hetnet's beneficial 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 Year AreaPowerConsumption[Watt/km2] wireless only Pbh arch1 Pbh arch2 Pbh arch3 η ∈[0.1, 0.6] is increasing with the same rate between 2010 and 2020 backhaul impact ~50%
  18. 18. Energy Efficiency Assessment Backhaul Power Consumption 18 Rural Areas Macrocell deployment Outdoor small cell deployment  Backhaul impact is limited only for macro BS deployment.  Small cell deployment can still provide lower consumption when the demand is high.  Wireless backhaul solutions are the least energy efficient.  Backhaul will be responsible of remarkable share.  It has to be included into the analysis. Wireless MBH solutions Coverage and capacity requirements are changing over the years.
  19. 19. Energy Efficient Solutions Architectural 19 0 5 10 15 20 25 30 0 500 1000 1500 2000 2500 NBS AreaPowerConsumption(Watt/km2) Transmit power dominant Baseline power is dominant Higher baseline  Tradeoff creates an optimum densification level.  Idle power consumption is a key parameter to define the optimum point.  Higher capacity requirement favors densification.  Careful prediction is the key.  What are the key design parameters?  How they impact the energy efficiency? 0 arg 1 ( ) (W,C ,R,..)backhaul m tot i p tx t et i P N P P P f = = ∆ + + =∑ 0 5 10 15 20 25 30 0 500 1000 1500 2000 2500 NBS AreaPowerConsumption(Watt/km2) 5Mbps/km2 20Mbps/km2 Higher capacity demand
  20. 20. Energy Efficient Solutions Architectural 20  How much we can save through Hetnet solutions?  Type of small BSs.  Number of small BS per macro BS.  Capacity requirement.  Indoor/outdoor user split.  Methodology  Ensure that each strategy has the same performance. 1000 1500 2000 2500 3000 3500 4000 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Distance (m) bits/s/Hz/km2 macro macro + 3 micro macro + 5 micro Find ISD that can satisfy the requirement 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 300 400 500 600 700 800 900 1000 1100 1200 1300 Distance (m) Watt/km2 macro macro + 3 micro macro + 5 micro Find the optimum ISD that minimizes APC ˆmin(D, *)optD D= ˆD *D Less need for macro densification
  21. 21. Energy Efficient Solutions Architectural 21 Scenario: Outdoor small cell deployment under macro-cellular coverage.  Uniform traffic scenario.  Full buffer traffic. 2 4 6 8 10 12 14 300 400 500 600 700 800 900 Area Throuhput [Mbps/km2 ] MinimalAreaPowerConsumption[Watt/km2] macro macro + 3 micro macro + 5 micro macro + 3 pico macro + 5 pico  Traditional deployments is only efficient when the demand is low.  Most efficient design is dependent on the demand. • 30% saving is feasible.
  22. 22. Energy Efficient Solutions Architectural 22 Scenario: Indoor small cell deployment under macro-cellular coverage.  Non-Uniform user distribution.  Co-channel deployment.  Significant improvement in user SE. • Wall elimination.  Low traffic region  Coverage limited • Femto deployment does not pay off.  High data rate requirement reverses the conclusion.  Blasting the signals over the walls is shown to be neither energy efficient nor feasible to satisfy the growing capacity demand. 0 1 2 3 4 5 6 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 User Spectral Efficiency [bps/Hz] CDF ρp =0 ρp =0.2 ρp =0.4 ρp =0.6 ρp =0.8 ρp =1 macro-femto macro-only 10 100 -60 -40 -20 0 20 40 60 80 Area Throughput (Mbps/km2 ) PowerSavings(%) Macro+Femto ρ=0.2 Macro+Femto ρ=0.6 Macro+Femto ρ=1 Beyond 2015 ~2010
  23. 23. Energy Efficient Solutions Operational 23  How much we can save through Cell DTX for a given traffic pattern? ( ) 24 0 0 1 1 1 ( ) (1 ) 24 BSN t t tot p tx BS i i t i P P N P Pη δ η = =  = ∆ + + − ∑∑ 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 0 50 100 150 200 250 T [Hours] AreaPowerConsumption[W/km2] Saving due to Cell DTX for a given deployment  Optimized deployment + apply cell DTX  Significant saving.  Incorporating cell DTX at the planning stage brings 40 percent more saving.  By deploying slightly faster than actual requirements. Cell DTX  We proposed a Quantitative method 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 0 50 100 150 200 250 T [Hours] AreaPowerConsumption[W/km2] Saving due to energy-aw are deployment
  24. 24. 5 10 15 20 25 30 35 40 45 50 0 500 1000 1500 2000 2500 Number of BSs TotalCost[kEuro] 0 20 40 60 0 10 20 30 40 50 Energy Cost Total Cost Optimum Analysis on Energy-Cost Tradeoff Main Tradeoffs 24  How does the key cost elements impact the future design of green networks? infra (N , W,P )tot spectrum energy BS totC C C C f= + + = Key cost elements: More spectrum. Energy minimization ≠ Cost minimization Spectrum has the significant impact on energy and cost.  Secondary spectrum access, high frequencies can be the solution.
  25. 25. Analysis on Energy-Cost Tradeoff Economic Viability Analysis 25  Under which circumstances will an operator will get a total cost saving from EE solutions? 1 i i i tot BS ref ref ref tot BS C c N C c N =   Methodology  Economic viability method using NPV 1 1 (1 ) N n n n c c d − = = + ∑ Existing Deployment  Solution: Hardware upgrade with cell DTX capability  Investment cost per BS:  Analysis:  What is the break-even cost of new hardware? Greenfield Deployment  Solution: Energy efficient deployment  Have higher initial investment cost.  Analysis:  How expensive energy cost must be EE design brings TCO saving? c∆ 2 Case Studies Both CAPEX and OPEX
  26. 26. ( ) 11 (1 ) ref N n n n BS cnn e E E N d −= − > ∆ + ∑ Analysis on Energy-Cost Tradeoff Economic Viability Analysis 26 Existing Deployment  Solution: Hardware upgrade with cell DTX capability 0 0.5 1 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 δen [Euro/kWh] Break-evencost(∆c/ccapex) Mature markets Developing countries  Upgrading the hardware is more cost-effective as energy cost increases.  Significant saving by cell DTX (up to 60%) can compensate the additional investment cost. 0.08break even c capexc− ∆ ≈ × 0.42break even c capexc− ∆ ≈ × ( ) 11 (1 ) ref N n n n BS cnn e E E N d −= − > ∆ + ∑
  27. 27. Analysis on Energy-Cost Tradeoff Economic Viability Analysis 27 Greenfield Deployment  Solution: Energy efficient greenfield network deployment ( )1 2 1 11 1 ( , ) ( , ) ' ( ) ( ) (1 ) (1 ) ref i N N n tot tot opexe c BS BS capext nn n e E t E t c t N N c d d ρ ρ − −= = −   > − +  + +  ∑ ∑ Saving Additional Cost 0 5 10 15 0 5 10 0 5 10 15 20 25 30 Time [Years]1/en [kWh/Euro] KEuro/km2 Energy Saving  Clean Slate energy efficient deployment might compensate the additional capital investments.  However, annual increase in OPEX reverses the situation.  Over-dimensioning might not be motivated for total cost saving.  Unless operators get additional benefits from energy saving. 0 5 10 15 0 5 10 0 5 10 15 20 25 30 Time [Years]1/en [kWh/Euro] KEuro/km2 Energy Saving Incremental increase in CAPEX 0 5 10 15 0 5 10 0 5 10 15 20 25 30 Time [Years]1/en [kWh/Euro] KEuro/km2 Energy Saving Incremental increase in CAPEX Incremental increase in OPEX 0 2 4 6 8 10 10 20 30 0 1 2 3 4 5 copex [KEuro]ccapex [KEuro] Breakevencostofelectricity[Euro/kWh]
  28. 28. 2 Thesis Focus & Research Questions 1 Motivation 3 Key Findings 4 Conclusion
  29. 29. Conclusions 29 1. How to assess the energy efficiency of a given network?  Energy efficient does not always mean lower energy consumption.  Both coverage and capacity should be considered to avoid disputable indication.  Backhaul will potentially become a bottleneck for future green networks.  Technology and topology choices are highly important. 2. How should wireless access networks be deployed and operated in an energy efficient manner?  Energy-oriented clean slate deployment brings significant savings.  Key design parameters: Idle/transmit power ratio, capacity requirement.  Cell DTX is a promising hardware improvement enabling up to 60% savings.  Consider the fact: Deployment and Operation are highly dependent. 3. What are the consequences of energy efficient solutions on total cost?  Energy minimization does not mean total cost saving.  Applying sustainable solutions might also bring total cost reduction.  Viability of the solutions must be assessed case by case.
  30. 30. 30 Thank you for your attention. Any questions?.... OR NOT?
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