Transcript Slide 1

Research Issues for Energy Efficient
Cellular Networks*
by
Vijay K. Bhargava
University of British Columbia
Vancouver, Canada
IEEE Communications Society President
_____________________________________________
* E. Hossain, V. K. Bhargava, and G. Fettweis (Eds.), “ Green Radio
Communication Networks,” Cambridge University Press, July 2012.
Z. Hasan, H. Boostanimehr, and V. K. Bhargava, "Green cellular networks:
a survey, some research issues and challenges", IEEE Communications
Surveys and Tutorials, 13(4), 524-540, November 2011.
Presentation Outline
 Introduction
 Energy Efficiency Metrics
 Architecture
 Energy Savings in Base Stations (BS)
 Network Planning
 Heterogeneous Network Deployment
 System Design
 Green Communication via Cognitive Radio
 Cooperative Relays to Deliver Green Communication
 Energy Efficiency of future generation wireless systems based on
Cognitive and Cooperative Networks
 Some Broader Perspectives
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The University of British
Columbia
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The IEEE Communications Society
 Second largest in the IEEE family with about 50,000 members.
 Journal Portfolio.
 Conference Portfolio.
 Standard Activities.
 Chapter Activities:
 In Austria ComSoc has 164 members.
 In Poland ComSoc has 143 members with a majority of them
concentrated in Warsaw, Krackow and Poznan.
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Introduction:
Growth in Cellular Data Traffic
 Tremendous growth in cellular data traffic due to Android and
iPhone devices, iPad and Kindle and success of social networking
giants like Facebook.
 Number of pages viewed on the Opera mobile browser grew from
1.8 billion pages in January 2008 to 109 billion pages in April 2012.
 Since April 2011, page views increased by 88.2%.
 The Technology news website Techcrunch reported that mobile
data traffic grew 2.3 fold over 2011, more than doubling for the
fourth year in a row (grew by 133%).
 Based on the current rate of change and adoption, Google
predicts that more people will use their mobile phone than PCs to
get online by 2013.
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Introduction:
Growth in Cellular Phones
 In Oct. 2012, BBC reported that total number of mobile phone
connections worldwide has reached over 6 billion (ITU).
 The main source of growth is in Asia-Pacific region including
developing economies like India and China with one billion
subscriptions each.
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Introduction:
Cellular Energy Consumption
 Information and Communication Technology (ICT) represents
around 2% of total carbon emissions. Mobile networks consume
about 0.2% and fixed networks 0.4%, the remaining 1.4% being IT.
 In developing markets, huge growth in the number of off-grid
BSs, typically powered by diesel generators from 290,000 in 2007
to 640,000 in 2012, and consuming $14.6 billion worth of diesel.
 Mobile network energy consumption currently stands at 100 Tera
Watt-Hour per year worldwide and adds significantly to network
operational expenditures (OPEX).
 Energy efficiency is not addressed swiftly in future wireless
networks, the environmental and financial impact could be high.
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Introduction:
Cellular Energy Consumption
Power consumption of a typical wireless
cellular network.
Power consumption distribution in radio base
stations.
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Taxonomy of the presentation
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Energy Efficiency Metrics
 Energy Efficiency Metrics are used to:
 compare and assess the energy consumption of various components
and the overall network.
 set long term research goals of reducing energy consumption.
 Metrics can be defined:
 either by the ratio of output and input power.
 or by the ratio of some measurable performance to the input energy
(e.g bits/Joule).
 Defining metrics at component level is easy. While, it is more
challenging to define metrics at a system or network level.
 Due to the variety of network types and objectives defining one
single metric is doubtful.
 To asses true “Greenness” metrics must also consider:
 Deployment costs
 QoS requirements
 Spectral efficiency, and …
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Energy Saving in BS:
Power Amplifier
 Three essential parts of a BS: radio, baseband and feeder.
 Radio consumes more than 80% of a BSs energy requirements,
out of which, power amplifier (PA) consumes almost 50%.
 Modern BSs are inefficient because of their need for amplifier
linearity and high peak-to-average power ratio (PAPR).
 To obtain high linearity, PAs have to operate well below
saturation, resulting in poor power efficiency.
 PAs based on digital pre-distorted Doherty-architectures, GaN
(Aluminum Gallium nitride) and switch-mode seem to be more
promising.
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Energy Saving in BS:
Power Saving Protocols
 In current cellular network architectures, BS and mobile terminal
continuously transmit pilot signals.
 An intuitive way to save power is to switch off the transceivers
whenever there is no need to transmit or receive.
 LTE standard introduces power saving protocols for the mobile
handset:
 Discontinuous Reception (DRX) mode.
 Discontinuous Transmission (DTX) mode.
 IEEE 802.16e or Mobile WiMAX has similar provisions for sleep
mode mechanisms for mobile stations.
 Power saving protocols for BSs need to be developed in future.
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Energy Saving in BS:
Power Saving Protocols
 Cellular traffic varies spatially and temporally per hour.
 BSs operate inefficiently under low load conditions especially
during the nighttime, since base stations still have to send control
signals.
 Switching off BSs under low load and let other BSs take care of
remaining users could save energy.
 Niu. et. al propose cell zooming concept through which BSs can
adjust the cell size according to traffic situation:
 Cells can zoom in or out by a variety of techniques such as physical
adjustment of antenna, BS cooperation and relaying.
 Cell Zooming could potentially reduce the energy consumption and
help in load balancing.
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Energy Saving in BS:
Other ways to reduce energy consumption
 Reducing number of BSs:
 Saving energy using ways such as 2-way and 4-diversity, feeder
less site, extended cell, low frequency band, 6-sector site and
smart antennas.
 Using Renewable Energies:
 In remote Africa, the cost of running a base station on diesel
amounts to $30,000 per year.
 Renewable energy resources such as biomass, biofuels, solar and
wind are feasible choices for BS sites.
 Pike Research forecasts that renewable energy will power 4.5
percent of the world's mobile BSs by 2014, up from 0.11% in 2010.
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子曰：三人行必有我师焉
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Heterogeneous Network Deployment
A typical heterogeneous network may look like:
Macrocell~1-30km, Microcell~200-2000m, Pico-cell~4-200m, Femtocell~order 10m
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Heterogeneous Network Deployment
 An obvious way to increase power efficiency is to decrease the
propagation distance between nodes.
 Cellular network deployment solutions based on smaller cells
such as micro, pico and femto-cells are very promising to save
energy.
 Many challenges exist in deployment, such as:
 Coexistence with macrocell and cross-tier interference.
 Whether to offer licensed and unlicensed spectrum to smaller cells.
 Optimal deployment strategies needed since deploying too many cells
may reduce overall efficiency of macrocell BS.
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Power Allocation in Heterogeneous
Networks
 Deployment of large number of low power nodes (micro, pico,
femto) among high power macro nodes introduces severe
interference problems.
 Interference is even more severe is case of co-channel deployment
scenario.
 Interference leads to high outage and power consumption at the
user’s end which decreases network overall capacity.
 Therefore, it is important to develop smart power allocation
schemes for interference mitigation and power efficiency.
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Power Allocation in Heterogeneous
Networks
 Benefits provided through power allocation:
 Allows network users to consume only sufficient power needed to
meet the desired quality of service (QoS), which leads to efficient
energy consumption.
 Prolongs battery life of mobile equipment.
 Improves network capacity and link QoS.
 We have proposed a multi-objective optimization scheme to
achieve optimal power allocation in heterogeneous networks where
we jointly minimize the total power consumption at transmitter and
maximum allowed outage probability at the receiver.
______________________________________________________
* S. N. Pradhan, V. K. Bhargava, “Multi-objective optimization for power allocation in
heterogeneous cellular networks”, under preparation.
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Green Communication via Cognitive Radio
 Main focus of Cognitive Radio:
 Radio spectrum is one of the scare and most valuable resources in
wireless communications.
 Actual measurements have shown that the most of the allocated
spectrum is under-utilized.
 Spectral efficiency can be increased significantly
opportunistic access of the frequency bands to other users.
by
giving
 How can it be useful in terms of energy saving?
 Capacity increases linearly with Bandwidth but only logarithmically
with Power.
 Cognitive Radio increase spectral efficiency, thus less power can be
used for a certain transmission rate.
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Green Communication via Cognitive Radio
 However, Cognitive Radio has a broader definition:
 A cognitive radio is aware of its own capabilities and the needs of its
users (AWARENESS).
 It can measure the parameters in the environment (COGNITION).
 Based on these parameters, it can intelligently modifies its
functionality in order to achieve an objective (RECONFIGURABILITY).
 One of these objectives can be power saving.
 Many techniques have been proposed in literature to reduce
energy consumption via Cognitive Radio.
 They are complex and expensive.
 More feasible solutions must be proposed in future.
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Cooperative Relays to deliver Green
Communications
 Establishing a reliable connection to a distant node via direct
transmission needs high amount of power.
 On the other hand, Cooperative communications extends the
coverage by:
 Avoiding large power losses in long distances.
 Elimination of shadowing effect.
 Also, it has been shown in literature that relaying techniques can
result in extended battery life.
 For instance, multi-hop communication, as a particular case of
cooperative communications:
 Divides the direct paths to several shorter paths.
 Each path has a better quality.
 Less power is needed to communicate reliably in these shorter paths.
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Cooperative Relays to deliver Green
Communications
 There are two different approaches
techniques in order to minimize energy:
exploiting
Cooperative
1. Installing fixed relays:
 The idea is installing relays instead of new BSs to make the cells
smaller and denser.
 Relays are cheaper, and less complex in many ways.
2. Introducing user cooperation:
 Users can help each other by sending and receiving each other
messages to and from BS.
 Some users might be selfish and not willing to sacrifice their
power for another user.
 In a very recent work by Noklebly and Aazhang, an algorithm is
proposed which gives the incentive to the users to act as relays,
while overall energy efficiency is improved.
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Energy Efficiency of future generation
wireless systems based on Cognitive and
Cooperative Networks
 Cognitive Radio and Cooperative communication are becoming
key technologies to address the power efficiency of a cellular
network.
 European Union has started C2POWER project with objectives to
reduce power consumption of mobile terminals using cognitive
and cooperative technologies.
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Energy Efficiency of future generation
wireless systems based on Cognitive and
Cooperative Networks
 Addressing energy efficiency of heterogeneous networks based
on cooperative and cognitive networks:
1. Low Energy Spectrum Sensing:
 It is necessary to design energy-efficient sensing schemes so that
improvement in data rate due to opportunistic spectrum access
does not increase energy consumption significantly.
 On going and possible research topics are:





Low complexity cyclostationary detectors.
Conditions under which cooperative sensing is more efficient.
Cluster based designs to reduce power consumption.
Sequential detection techniques.
Compressive sensing.
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Energy Efficiency of future generation
wireless systems based on Cognitive and
Cooperative Networks
2. Energy-Aware Medium Access Control (MAC) and Green Routing:
 Medium access control (MAC) in cooperative and cognitive
wireless systems introduces new challenges not seen in traditional
wireless systems.
 In addition to MAC design, proper routing schemes will also be
necessary to achieve desired end-to-end QoS.
 Little research has been done regarding the energy efficiency of
such systems.
 Future MAC protocols that employ HARQ protocols have potential
to reduce energy cost.
 For routing, it is necessary to explore analytical models that can
quantify trade-offs between energy saving and end-to-end QoS
performance.
 ROLL working group of IEEE is looking at routing protocols for low
power and lossy networks.
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Energy Efficiency of future generation
wireless systems based on Cognitive and
Cooperative Networks
3. Energy-Efficient Resource Management
Heterogeneous network deployment:
and
applications
 Investigating relaying mechanisms and resource
schemes that minimize energy consumption.
in
allocation
 Need to answer three fundamental questions: “ where to place
relays”, “whom to relay”, and “when to relay”.
 Need to investigate low power consumption based scheduling
mechanisms in presence of multiple cognitive users.
 How to design energy aware heterogeneous networks, where the
macrocell and femtocell coexist for co-channel deployment.
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Energy Efficiency of future generation
wireless systems based on Cognitive and
Cooperative Networks
4. Cross-Layer Design and Optimization:
 Need energy-efficient cross-layer schemes optimizing resources in
various layers while considering the channel quality as well as the
network traffic.
 Need holistic control algorithms (from cross-layer perspective)
which adapts the system to the dynamics (mobility of users,
nature of modern applications, propagation environment and
application requirement – all time varying in nature) at runtime.
 Cross-layer design may be crucial in the use of cooperative
relaying to improve spectrum diversity in CR networks.
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Energy Efficiency of future generation
wireless systems based on Cognitive and
Cooperative Networks
5. Addressing Uncertainty Issues:
 Need to investigate robustness of energy-efficient schemes with
uncertain environments (imperfect CSI, imperfect sensing etc.).
 Need to compare performance
uncertain environment.
with traditional
schemes
in
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Some Broader Perspectives
Statistical Power Profiles
 The traffic pattern is dramatically different depending on the time
of the day or geographical location.
 In a broader perspective, there can be a data-base in BS and
mobile terminals, in which the traffic pattern during different
times of the day is saved.
 Based on the obtained statistics, dynamic algorithms can be
designed to switch the BS or mobile terminal to a different power
profile appropriate for that time of the day.
 Potential to save 25% to 50% of energy.
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Some Broader Perspectives
Smart Grids
 Smart grid has emerged to coordinate the power generators,
transmission systems and appliances utilizing two-way
communication lines between all these different entities.
 Absorbing BSs in a smart grid can exceedingly increase the
power efficiency without adversely affecting the QoS and
capacity.
 Measurement sensors can update the status of BSs, and then
transmit them to the smart grid control system, thereby
improving the energy efficiency.
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Some Broader Perspectives
Embodied Energy vs. Operating Energy
 Almost all the research on Green communications results in
larger number of BSs with lower powers, since the objective is
decreasing the Operational Energy.
 Producing new and
(Embodied Energy).
sophisticated
BSs
consumes
energy
 Considering embodied energy and operational energy results in
solutions which disagree with increasing the number of BSs and
lowering their power.
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Conclusions
 Tremendous growth in cellular industry demands energy saving
measures to be taken to maintain profitability and to reduce
environmental impact.
 BSs account to a major portion of energy consumption in a
cellular network and we need new hardware and system level
features to improve efficiency.
 Heterogeneous network deployment strategies must be devised.
 Cognitive Radio and Cooperative Communications can provide
savings in terms of energy.
 Broader perspectives and other paradigm-shifting technologies to
further reduce energy consumption.
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Acknowledgments
 This research was
Engineering Research
strategic project award
Bell Canadian Graduate
supported by the Natural Sciences and
Council of Canada (NSERC) under their
program and in part by Alexander Graham
Scholarship awarded to Ziaul Hasan.
 Ekram Hossain, Vijay Bhargava, and Gerhard Fettweis (Eds.),
“Green Radio Communication Networks,” Cambridge University
Press, July 2012.
 Ekram Hossain, Dong In Kim, Vijay Bhargava (Eds.),
“ Cooperative Cellular Wireless Networks, ” Cambridge University
Press, March 2011.
 Ekram Hossain, Vijay Bhargava (Eds.), “ Cognitive Wireless
Communication Networks,” Springer, 2007.
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