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© University of Cancun, Mexico 1
Chapter 21: Overview of Energy Saving
Techniques for Mobile and Wireless Access Networks
1 Diogo Quintas, 1Oliver Holland, 1Hamid Aghvami, and 2Hanna Bogucka
1Centre for Telecommunications Research, King’s College London
2Poznan University of Technology, Poland
HANDBOOK ON GREEN INFORMATION AND COMMUNICATION SYSTEMS
© University of Cancun, Mexico 2
Carbon Footprint of Mobile Networks
Embodied Energy Energy spent on manufacturing,
installation and decommission of equipment
Operational Energy Energy spent on the day to day
operation of the equipment
Operational Energy is the dominant part of the energy consumption… but,
As systems become more efficient the Embodied Energy will be dominant
4.3 kg CO 2
8.1 kg CO 2
9 kg CO 2
2.6 kg CO 2
0
2
4
6
8
10
12
14
Base Stations Handsets
CO2
Emis
sion
s pe
r Sub
crib
er p
er y
ear
Operational
Embodied
Figure 1: Contribution to the carbon footprint of mobile wireless networks [1]
© University of Cancun, Mexico 3
Operational Energy
There are three main components of energy consumption by access equipment: Power Amplifiers Cooling Baseband Processing Other circuitry
The total power consumption has a load and RF power variant part AND a fixed consumption
Figure 2: Operational energy consumption breakdown [2]
© University of Cancun, Mexico 4
Operational Energy Modeling
Linear models scaling with the average RF power consumption and load have been proposed in the literature, modeling a Omni-directional BS* [3]:
lPP rft )1(
Parameter Typical Values found in Literature [3-6]
PA Efficiency () 3.1-7.8 (Macro BS), 4-5.5 (Micro BS)
Fixed power () 83-300 (Macro BS), 32-68 (Micro BS)
Proportional to load () Not scalable (Macro BS), ~0.5 (Micro BS)
* - The total power typically scales linearly with the number of PA’s and sectors
© University of Cancun, Mexico 5
Embodied Energy
Estimatives for the embodied energy of a base station set the total cost as 75GJ [7]
Semiconductor manufacure is the dominant factor in the embodied energy of mobile equipment
Figure 3: Embodied energy consumption breackdown [7]
© University of Cancun, Mexico 6
Towards a Life Cycle Perspective
To evaluate the enviormental impact of a new system design it is critical to have in mind the full life cycle‘s energy consumption
Facilitating the comparison between two systems/techniques with different life expectancie‘s (or time frames...) the full life cycle‘s energy consumption must be scaled into an energy cost per unit of time (usually measured in years)
© University of Cancun, Mexico 7
Extending the Life Cycle
Modular equipment with multiple reusable parts Parts of High end equipment could be reused in
lower end equipement after reaching their end of life.
Reconfigurable chips New technology could then be deployed by a
simple reconfiguration of the chip
Recycling valuable raw material In practice this is already done...
© University of Cancun, Mexico 8
Improving Hardware
Improvements on hardware design are the most effective way of reducing the operational energy consumption
Base station equipment consuming just 500W has been released by manufacturers
Little understanding of the impact of the new design paradigms in the manufacture phase
© University of Cancun, Mexico 9
Power Amplifiers
Three promising designs/techniques:
Doherty Amplifiers Envelope Tracking Digital Pre-distortion
Together these are expected to yield efficiency rates of up to 50% [8]
Comercial PA‘s have been anounced with an efficiency rate of 45%
© University of Cancun, Mexico 10
Processors
Power consumption of a processor varies quadraticaly with the voltage and linearly with the clock frequency
Dynamicaly adaptin the frequency and undervolting the processor leads to significant power savings
Multi core arquitechtures allow a fine-grained control off the power consumption
© University of Cancun, Mexico 11
Micro Sleep Modes
Switch off signaling during some timeslots
Power down the processor (under voltage)
Switch off the PA (DTX)
Ensure that the power consumption scales with the effective load (i.e. the instantaneous load).
© University of Cancun, Mexico 12
Whole System Design
Component level efficiency improvements can only reduce the operational power costs There are fundamental limits to achievable
efficiency gains by better designs They do little to improve the Energy
Consumption/Capacity trade off
The whole system has to be taken into consideration Network dimensioning Alternative networking paradigms Spectrum management
© University of Cancun, Mexico 13
“Green” Radio Interface
Theoretical capacity of current modulation schemes are pushing us closer to the Shannon bound. As the bound is approached the number of base
stations to provide capacity is reduced...
However, these new techniques require complex DSP, increasing both the embodied and operational energy of processors.
Simpler techniques are needed that still achieve capacity...
© University of Cancun, Mexico 14
System Dimensioning
Smaller cells tend to consume less RF power - however more base stations are needed to cover the same area
The fixed energy costs increase linearly with the number of access routers
For smaller micro base stations the embodied starts to dominate the Life Cycle consumption
Figure 8: Energy consumption per year to cover a 20 sq km area, with and without embodied energy
© University of Cancun, Mexico 15
Multi Hop Networks
Multi hop networking can effect a reduction by:
Increasing the capacity density of the network Decreasing the RF power levels in the network
However, relays can be inthemselves power hungry
The embodied energy of relays could be a problem.
© University of Cancun, Mexico 16
Relay Aided Networks
The operational power consumption can be reduced up to a factor of 10 depending on the required capacity density
Extrapolating from an economic analysis, if relays have an life cycle cost of less than 6% of a base station then energy is saved
Relay switch off paterns can further reduce the life cycle costs of these networks.
© University of Cancun, Mexico 17
Mobile Ad-Hoc Networks
Delay tolerant applications can use Mobile Ad-Hoc networks
Traffic can be shifted from the access network to the Ad-Hoc network, reducing the capacity density required
Effects on the energy efficiency are highly dependent on the spatial and temporal characteristics of delay tolerant traffic...
© University of Cancun, Mexico 18
Dynamic Spectrum Management
Utilizing the available spectrum bands in a more intellegent way can reduce energy consumption by: Moving users or traffic from one band to another
switching off all radio equipment in one of the bands
Adjusting sectorisation patterns allowing the switching off of some sectors
Moving users or traffic between bands to allow subsets of cells to be switched off
Enabling the switching off radio equipment in single band scenarios
© University of Cancun, Mexico 19
Alternative Source of Energy
Grid access is an increasingly important issue as mobile networks grow in emerging markets
On-site generation has to be used, bypassing the need for a grid (and associated losses...)
Coupled with an effective reduction of the power consumption of access networks, renewable energy is an option to reduce the carbon footprint
© University of Cancun, Mexico 20
Suitability Of Wind and Solar Power
0
2
4
6
8
10
12
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Wind Power (kWh)
Solar Power (kWh)
Total (kWh)
Macro sites have more space to deploy power generating equipment
BUT... consume much more power.
Figure : Energy availability throughout the year in London, United Kingdom. Data from
Energy yields from renewable source can be volatile, with clear seasonal patterns
© University of Cancun, Mexico 21
Conclusion
There are several techniques that can improve the access network‘s energy efficiency spanning several design dimensions:
Component level energy efficient design Network planning Spectrum management Renewable energy
Little research has been done from a life cycle prespective – recent energy efficient research has been focusing on the operational energy reduction
There is a risk of shifting the energy consumption of the operational phase to the manufacture phase.
© University of Cancun, Mexico 22
Selected References[1] T. Edler, “Green base stations how to minimize co2 emission in operator networks.” in
Next Generation Networks and Base stations Conference, Bath, UK, 2008.[2] H. Karl, “An overview of energy-efficiency techniques for mobile communication System,”
TU Berlin, Tech. Rep., 2003.[3] O. Arnold, F. Richter, G. Fettweis, and O. Blume, “Power consumption modeling of different
base station types in heterogeneous cellular networks,” in Future Network and Mobile Summit 2010
[4] M. Deruyck, E. Tanghe, W. Joseph, and L. Martens, “Modelling and optimization of power consumption in wireless access networks,” Comp Comms, In Press, Corrected Proof, 2011.
[5] W. Guo and T. OFarrell, “Green cellular network: Deployment solutions, sensitivity and tradeoffs,” in WiAd 2011, Jun 2011.
[6] L. Saker and S. Elayoubi, “Sleep mode implementation issues in green base stations,” in PIMRC 2010, sept. 2010, pp. 1683 –1688.
[7] I. Humar, X. Ge, L. Xiang, M. Jo, M. Chen, and J. Zhang, “Rethinking energy efficiency models of cellular networks with embodied energy,” Network, IEEE, vol. 25, no. 2, pp. 40 –49, march-april 2011.
[8] L. Correia, D. Zeller, O. Blume, D. Ferling, Y. Jading, I. Go anddor, G. Auer, and L. Van Der Perre, “Challenges and enabling technologies for energy aware mobile radio networks,” Comm Mag, IEEE, vol. 48, no. 11, pp. 66 –72, november 2010.
© University of Cancun, Mexico 23
Thanks for your attention!