Network Energy Saving Technologies for Green Wireless Access Networks

IEEE Wireless Communications • October 201130 1536-1284/11/$25.00 © 2011 IEEE

PA

Idle

Transceivers

RBS

Transmission/aux (optional)

(TXM)

INTRODUCTION

The mobile industry faces a critical energy con-sumption challenge. Anticipated by Gartner [1],by 2013 smartphones will exceed 1.82 billionunits and surpass PCs as the most common webaccess devices. Consequently, more wirelessinfrastructures have to be deployed with largedemands on energy. Meanwhile, data-intensiveservices are beginning to dominate mobile ser-vices. The network data volume is expected toincrease by a factor of 10 every five years, associ-ated with a 16–20 percent increase of energyconsumption [2]. Applying this rate to mobilecommunications, which contribute 15–20 percentof the entire information and communicationstechnologies (ICT) energy footprint and 0.3–0.4percent of global CO2 emissions [2], the mobile

industry faces a great sustainable developmentproblem in energy consumption. It is crucial todevelop energy-efficient wireless technologies tomeet this challenge.

We study in this article the energy efficiency(EE) of the wireless access network, which isbroadly defined as any wireless system usingradio base stations (RBSs) or access points(AP) to interface mobile devices with the corenetwork or Internet. The reasons to focus onwireless access networks are following. First,since wireless access networks are the mostwidely deployed wireless networks in the world,energy-efficient solutions designed for wirelessaccess networks are expected to significantlyimprove EE in the ICT sector. Second, as along tradition, the standards of wireless accessnetworks are mainly focused on throughputperformance. Only recently has EE beenreceiving increasing attention. Significant stud-ies are needed to balance performance andEE. Third, the demand from mobile users forEE is urgent in order to enjoy better mobileservices.

As shown in Fig. 1, statistics indicate that theRBS is the main source of energy consumptionin the network of a mobile operator [3]. Energy-efficient solutions for wireless access networksare mainly concentrated on RBSs. Among allcomponents in an RBS, power amplifiers (PAs)drain the most energy. Energy is also dissipatedin alternating current/direct current (AC/DC)converting, cabling, and cooling. Various solu-tions have been proposed to improve EE of theRBS, such as increasing PA efficiency, usingnon-active cooling techniques, employing mast-head PA to reduce feeder loss, exploiting energyefficient backhaul solutions, applying energy-effi-cient deployment strategies, and introducingenergy-efficient protocols. This article overviewssoft methods to improve EE of RBSs, with anemphasis on Long Term Evolution (LTE) sys-

TAO CHEN, VTT TECHNICAL RESEARCH CENTRE OF FINLANDYANG YANG, SHANGHAI RESEARCH CENTER ON WIRELESS COMMUNICATIONS, CAS SHANGHAI INSTITUTE OF MICROSYSTEM AND INFORMATION TECHNOLOGY

HONGGANG ZHANG, ZHEJIANG UNIVERSITYHAESIK KIM, VTT TECHNICAL RESEARCH CENTRE OF FINLAND

KARI HORNEMAN, NOKIA SIEMENS NETWORKS

ABSTRACTThe energy consumption problem in the

mobile industry has become crucial. For the sus-tainable growth of the mobile industry, energyefficiency (EE) of wireless systems has to be sig-nificantly improved. Plenty of efforts have beeninvested in achieving green wireless communica-tions. This article provides an overview of net-work energy saving studies currently conductedin the 3GPP LTE standard body. The aim is togain a better understanding of energy consump-tion and identify key EE research problems inwireless access networks. Classifying networkenergy saving technologies into the time, fre-quency, and spatial domains, the main solutionsin each domain are described briefly. As present-ly the attention is mainly focused on solutionsinvolving a single radio base station, we believenetwork solutions involving multiplenetworks/systems will be the most promisingtechnologies toward green wireless access net-works.

NETWORK ENERGY SAVING TECHNOLOGIES FORGREEN WIRELESS ACCESS NETWORKS

The authors providean overview of network energy saving studies currently conductedin the 3GPP LTEstandard body. Theaim is to gain a better understandingof energy consump-tion and identify keyEE research problemsin wireless accessnetworks.

TE C H N O L O G I E S F O R GR E E E N RAD IO

CO M M UNICAT ION NETWORKS

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IEEE Wireless Communications • October 2011 31

tems. Soft methods do not upgrade hardware,but tune parameters in protocols, and applyenhanced architecture and deployment strategiesfor EE improvement. They enable flexible andcost-efficient solutions with minimum impact onhardware implementation.

UNDERSTANDING ENERGY EFFICIENCY

It is worth understanding EE before introducingenergy saving techniques. In the field of engi-neering, a system is usually designed to trans-form energy to useful work. EE can therefore bedefined as the ratio of useful work to the totalsupplied energy. The useful work in a communi-cation system refers to the effort to deliver mod-ulated signals for information exchange.

The definition of EE varies according to mea-sured objects. There are two basic methods tomeasure EE. One way is to define EE as theratio of efficient output power/energy to totalinput power/energy. This definition is widelyused by systems and components such as powersupply, PAs, and antennas. The other waydefines EE as the performance per unit of ener-gy consumption. This is referred to as floating-point operations per second (FLOPS) in digitalsignal processing (DSP), million instructions persecond (MIPS) in computer systems, andthroughput (bits per second) in communicationsystems.

In a communication system information istransmitted in the form of modulated electrical,electromagnetic, or optical waveforms. Due tothe imperfection of electronic components, a sig-nificant part of energy turns into heat. More-over, in a wireless system, due to the open natureof the wireless medium, only part of the radiatedenergy reaches the receiver. Measurements showa Global System for Mobile Communications(GSM) RBS may only have EE of 3.1 percent[4]. It renders a prominent challenge to improvethe EE of wireless systems.

EE in a communication system is not a sim-ple problem. Information theory reveals someinsights on the complexity. According to theShannon formula, the EE of a communicationsystem based on the additive white Gaussiannoise (AWGN) channel can be written as

(1)

where R is the bit rate of information, P is thereceived power, B is the bandwidth, and N0 isthe noise power spectral density. The unit of theEE metric is then bits per joule, which indicatesthe information units transmitted per one energyunit. Equation 1 shows that if N0 is fixed, EE isthe function of power density P/B. There areseveral observations from Eq. 1:• ηEE does not monotonically increase with B or

P. In a practical system where the bandwidthis a less flexible parameter, the maximum EEof a system is hard to achieve.

• For a given rate R, using more bandwidthrequires less power. If the bandwidth is infi-nite, the required power is fixed to P = N0Rln2. This gives a hint to trade bandwidth withenergy.

• The objective to optimize throughput perfor-mance is normally conflict with that to maxi-mize EE. Balancing these two objectivescomplicates the system design.Note that Eq. 1 gives an EE model for a

generic communication system. For a wirelesssystem, EE also depends on distance, carrier fre-quency, efficiency of antennas, and so on. More-over, interference and fading make EE of awireless system vary according to the radio envi-ronment.

It should be also remarked that Eq. 1 is anideal model without considering the hardwareimplementation of a system. In reality, the cir-cuits of a system will turn a significant amountof energy into heat. Therefore P in Eq. 1 shouldbe replaced by the sum of the supplied powerof the RBS and user terminals. Indeed, in aRBS the energy transforming to heat dominatesthe energy consumption of the RBS. Reducingenergy wasted by RBSs becomes the main con-cern of energy saving in a wireless access sys-tem.

RBS ENERGY CONSUMPTION MODELTo understand energy consumption problems inRBSs, it is necessary to establish a generic ener-gy consumption model of the RBS. RBSs con-forming to the same standard but produced bydifferent manufacturers are likely implementeddifferently, and thus show different energy con-sumption profiles. The generic energy consump-tion model abstracts the main energyconsumption sources in an RBS, which helps toisolate energy consumption problems in andderive EE solutions for RBSs.

We use the EE model defined by the Euro-pean Telecommunications Standards Institute(ETSI) for wireless access network equipment[5]. ETSI has defined the common methods andpractices to model, measure, and evaluate theEE of RBSs in various wireless access networks,including GSM, wideband code-division multipleaccess (WCDMA), Worldwide Interoperabilityfor Microwave Access (WiMAX), and, addition-ally, LTE systems [5].

As shown in Fig. 2, an RBS site typicallycomprises RBS equipment and several infra-

ηEER

P

B

P

P

BN= = +

⎛

⎝⎜

⎞

⎠⎟log ,2

01

Figure 1. Energy consumption composition of a mobile operator [3].

Retail2%

Data center6%

Core network15%

20%

57%

Radiobasestation(RBS)

Mobile telephoneexchange (MTX)


IEEE Wireless Communications • October 201132

structure support systems. RBS equipment is anetwork component that serves one or morecells and interfaces the mobile device throughan air interface and wireless network infra-structure. Radio transceivers, which includeradio frequency (RF) PAs, are key componentsin RBS equipment. Radio transceivers areresponsible for transmission and reception ofradio signals, as well as sending and receptionof signals to/from higher network entities. Toemphasize the impact of RF PA on the EE ofan RBS, the structure of transceivers is drawnin the model. A PA amplifies the signal fortransmission via antenna. In case of no trafficload, the RBS equipment could enter the idlemode by turning off the radio chains oftransceivers so that the power of the RBS couldbe saved.

Infrastructure support systems of an RBSinclude power supply, climate control, transmis-sion module, battery backup, and other auxiliaryequipment. The power supply connects to theAC power line or battery, and offers electricalenergy to the equipment; the climate controlmaintains the operating climate of the equip-ment within a defined range; the transmissionmodule connects the RBS to the core network;the battery backup supplies energy to the RBSwhen the AC power line is down. Figure 2 showsonly the outdoor reference model of a concen-trated RBS site. Note that an RBS can bedeployed indoors. Moreover, an RBS site may

be implemented in a distributed form whereremote radio heads (RRHs) are collocated withremote antennas. The indoor and distributedmodels are not depicted since they are similar tothe outdoor model.

The energy consumption profiles of typicalGSM [4] and third-generation (3G) [6] RBSs areprovided in Fig. 2. As we can see, the PAs of theGSM RBS consume 35 percent of the feedingpower. If the power efficiency of an RBS isdefined as the ratio of the radiated power to thefeeding power, the overall power efficiency ofthe GSM RBS is only 3.1 percent. By enhance-ment, the PA efficiency in a 3G RBS is boostedto 45 percent. The overall power efficiency of a3G RBS is 20 percent. The PA remains a bigproblem for the overall EE.

The PA is identified as the main cause of theEE problem in an RBS. Limited by material,implementation methods, dynamic operationrange, and other constraints, the efficiency ofRF power amplifiers normally ranges from 15 to35 percent. Advanced techniques like Dohertydesigns and envelope tracking designs are ableto boost PA efficiency up to 60 percent [7]. Inaddition, to improve the PA efficiency, an alter-native that comes at a high cost is to switch offPAs dynamically when possible (e.g., at idletimes of the RBS). This is a very promising ener-gy saving technique for an RBS. We describedifferent proposals based on this technique inthe next section.

Figure 2. Outdoor energy consumption reference model of a generic RBS site.

GSM

3G

3802

300

Examples of power consumption values of RBS (unit: watt)

*PA of RBS in GSM consumes 1320 watt power

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In addition toimprove the PA efficiency, whichcomes with highcost, an alternativeis to switch off PAsdynamically whenpossible, e.g. at theidle time of the RBS.This is a very promising energysaving technique for a RBS.

CHEN LAYOUT 10/11/11 1:26 PM 2


NETWORK ENERGY SAVING METHODSEnergy saving in an RBS is the key researcharea to improve EE of a wireless access network[5]. It has great potential to improve EE of anRBS. First of all, as shown in the previous sec-tion, the overall EE of an RBS remains low. Sec-ond, presently RBSs of all kinds are designed forbest performance, where EE is not the primaryconcern. As a result, the energy consumption ofan RBS does not scale with its traffic load butmaintains at a high level. As the traffic load of aRBS varies during the day, it gives clues to adaptthe power consumption of a RBS with its trafficload, through dynamically tuning the parametersof RBS and mobile devices. This approach iscalled the network energy saving method.

Network energy saving can be done by reduc-ing the operation time of PAs, shrinking theworking bandwidth, or even shutting down theRBS site [8]. Network energy saving methods,which are roughly classified into time, frequency,and spatial domains, are summarized in Fig. 3.There are also hybrid solutions that combinemethods from different domains. In the rest ofthe article, the main solutions are introduced.

Note that in this article the discussion on net-work energy saving is focused on the LTE sys-tem. This is because:• The maturity of 2G and 3G standards limits

the application of network energy savingmethods due to the backward compatibilityproblem.

• LTE and WiMAX are selected as the tech-nologies for the International MobileTelecommunications (IMT)-Advanced system,which is expected to be the mainstream futurewireless access system.

• Network energy saving studies on LTE arevery active in the Third Generation Partner-ship Project (3GPP) standards bodyIn the following, the term user equipment

(UE), which is used in LTE, refers to mobiledevices.

TIME DOMAINTime domain solutions in LTE temporally shutdown PAs in a RBS when in given time there isno data traffic in the downlink. Since those solu-tions are tightly related to the frame structure ofthe LTE system, it is necessary to provide a brief

introduction on the frame structure and controlsignals of LTE.

The downlink of LTE uses orthogonal fre-quency-division multiple access (OFDMA) tech-nology. As shown in Fig. 4, the channel accesstime of an LTE cell served by an RBS is struc-tured into contiguous time frames. Each frame isdivided into 10 subframes of 1 ms duration.Each subframe consists of two equal-sized slots.Each slot accommodates 6 or 7 symbols. In thefrequency domain, the system bandwidth isdivided into a set of subcarriers, each of whichhas a spacing of 15 kHz. Twelve consecutive sub-carriers in one slot are grouped into a physicalresource block (PRB), which is the basicresource unit allocated to a unit of UE. A sym-bol in a PRB is called a resource element of thePRB. The reference signals (RSs) and controlsignals occupy resource elements of a PRB in agiven pattern. They have to be transmitted regu-larly even when there is no data traffic in a PRB.If there is no or less downlink traffic, the fre-quency to transmit RSs and control signals canbe reduced. This is the principle for time domainenergy saving solutions. Accordingly the PAs canbe shut down temporally. The energy saving intime domain solutions can be measured by thetime fraction where PAs are off during a timeperiod, normally in a frame.

There are three basic ways to temporally shutdown PAs: turning off a PA in signal-free sym-bols; using a multicast broadcast single frequen-cy network (MBSFN) subframe to reduce RSs;and introducing the extended cell discontinuoustransmission (DTX) approach to further reduceRSs.

PA Off at Signal-Free Symbol — The most straight-forward approach is to turn off PAs in time peri-ods of a slot where downlink symbols aresignal-free. As shown in Fig. 4, in a normal LTEframe, which has 7 symbols per slot, 4 symbols ineach of subframes 1–4 and 6–9, 9 symbols insubframe 0, and 6 symbols of subframe 5 cannotbe signal-free due to the need to transmit RSsand control signals. Assuming it takes half of asymbol time to turn on a PA but the PA can beimmediately turned off, a simple calculationfrom Fig. 4 shows that at least 47 percent of thetime in a frame, PAs have to be on due to theneed to transmit RSs and control signals.

Figure 3. Network energy saving techniques for LTE.

Time

MBSFN

Frequency Space

HCS

Hybridsolutions

Extendedcell DTX

Layeredstructure

PA off atsignal-free

symbol

Bandwidthreduction

Carrieraggregation

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Network energy saving techniquesThere are three basic

ways to temporallyshut down PAs:

turning off a PA in signal-free symbols;

using a multicastbroadcast single-

frequency networksubframe to reduce

RSs; and introducingthe extended cell dis-continuous transmis-

sion approach tofurther reduce RSs.



MBSFN — The second approach uses the MBSFNstructure to reduce the number of RSs. MBSFNis proposed to deliver services such as mobileTV using the LTE infrastructure. In an MBSFNframe, the symbols for RS in subframes 1–4 and6–9 are reduced to 1. The PA operating timeduring a frame is then reduced to 28 percent.

Extended Cell DTX — The extended cell discontinu-ous transmission (DTX) approach [9], which iscurrently under discussion in 3GPP RadioAccess Network (RAN) Working Group (WG)1, is able to further reduce RSs compared to theMBSFN approach. As shown in Fig. 4, if there isno downlink traffic, in the extended cell DTXmode there is no need to have any transmissionin subframes 1–4 and 6–9 of a frame. The PAoperating time in a frame is further reduced to7.1 percent.

Time domain solutions are able to significant-ly reduce the PA operation time when a cell isidle. It is ideal to apply them on RBSs in ruralareas. In urban areas the idle traffic conditionrarely occurs during a day. Improvements areneeded, probably through joint time-frequencydomain scheduling, to make them also effectivein low traffic conditions. Moreover, time domainsolutions have to deal with backward compatibil-ity and UE performance problems [8]. The first

time domain approach is a pure implementation-based approach. MBSFN was included in LTERelease-8, and thus has no backward compatibil-ity problem. The extended cell DTX approach,however, requires changes in the standards. Fur-thermore, the reduction of RSs in the extendedcell DTX approach has a negative impact on theperformance of the UE. In LTE, some controlprocedures are performed with the assistance ofRSs. Without enough RSs, some UE may expe-rience unpredictable problems synchronizingwith an RBS or decoding control signals. Reduc-ing RSs may also prevent UE from entering intoterminal DTX mode and thus shorten its batterylife. Those problems have to be solved beforeapplying the extended cell DTX mode. Itdemands a new adaptive pilot design, in whichthe pattern of RSs is a function of the downlinktraffic load, and the states of UE and RBSs.

FREQUENCY DOMAINIn the frequency domain there are mainly twoapproaches to energy saving: bandwidth reduc-tion and carrier aggregation.

Bandwidth Reduction — Since the physical layerspecification of LTE supports a set of transmis-sion bandwidths, it is possible for an RBS tochange the channel bandwidth if needed. The

Figure 4. Reduce RSs of LTE frame in idle and low traffic load conditions.

1 frame (10ms)

1 subframe (1ms) 1 slot (0.5ms)

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bandwidth reduction technique adapts the band-width with the downlink traffic load. To main-tain the same power spectral density (PSD),smaller bandwidth requires less radiated power.If the downlink traffic is low, the channel band-width can be shrunk so that less power isrequired. Moreover, fewer RSs are needed forsmaller bandwidth. This further reduces thepower budget. For instance, when the channelbandwidth is changed from 10 MHz to 5 MHz,the RF transmission power could be reduced byaround 3 dB. There are mainly two ways toreduce bandwidth: shrink bandwidth but keepthe carrier frequency; or shrink bandwidth andchange the carrier frequency.

This approach is suitable for the low trafficload case. It is an implementation-basedapproach without the need to change standards.However, this approach does not shut downPAs. As an operating PA consumes much morethan an inactive PA, the energy saving from thisapproach may be marginal. Moreover, a PA nor-mally operates at an optimized point with agiven output power range. Reducing the outputpower will degrade the PA efficiency and in turncompromise the energy saving gain.

Carrier Aggregation — In the carrier aggregationapproach, it is assumed that in an RBS the carri-ers are aggregated by groups, and each group isserved by individual PAs. The idea is to shutdown the associated PAs when the correspond-ing aggregated carriers are not scheduled for thedownlink traffic. In this case this approach heav-ily relies on the implementation of the RBS. It isonly applicable to an RBS that has aggregatedcarriers and separate PAs attached to eachgroup of carriers.

In general, frequency domain solutions haveless impact on UE. However, due to the afore-mentioned constraints, the efficiency of frequen-cy domain solutions is limited. They are normallycombined with energy saving methods in otherdomains.

SPATIAL DOMAINThe aforementioned approaches in the time andfrequency domains are employed in a singleRBS. In the spatial domain, however, the solu-tions can be extended to heterogeneous net-works, and are therefore more flexible. Themain approaches currently used in the spatialdomain are reducing antenna number in an RBSand dynamically configuring cells in a multicellscenario. We propose a new approach that takesadvantage of traffic offloading in a layered struc-ture to reduce energy consumption of the wholenetwork.

Reduce Antenna Number — Reducing antenna num-ber is the most commonly used energy savingtechnique in the spatial domain. It works for thesituation where the traffic load of a cell is low.For instance, if the branches of antennas arereduced from 4 to 1, energy consumption oftransceivers is reduced to 1/4, as the PAs associ-ated with those branches can be switched off. Itcan combine with the bandwidth reduction tech-nique for the low traffic mode of an RBS.

The reduction of antenna branches decreases

the total output power and shrinks the cell size.Therefore, an additional mechanism is neededto maintain the strength of control signals at thecell edge. One straightforward way is to boostthe power of RSs and control signals so as tomaintain the cell size.

The antenna number reduction approach maylead to service degradation or interruption as theantenna reconfiguration is needed. In a normaloperation of a RBS, the antenna port number isassumed to be fixed during all active time of theRBS. The change of the antenna number shouldnotify UEs properly. Otherwise it will impactUE’s behaviors. It is suggested to use thisapproach in the semi-static load case.

Switch On/Off Cell — The cell switch-off approach[10] is a system-level approach that works in anarea covered by multiple cells, where those cellsmay use different radio access technologies(RATs). This approach has no need to modifythe low-layer components in the RBS. When thetraffic load in a given area is low, some cells canbe shut down, and the served UE units are hand-ed over to the remaining cells. Those inactivecells can be turned on during the busy time, sig-naled by neighboring working cells or the opera-tions, administration, and maintenance (OAM)layer of the system. There are two ways to switchon/off cells. One is signaling directly betweenRBSs. The other is dedicated control from theOAM layer of the system.

A special case of the cell switch-off approachis called the hierarchical cell structure (HCS)approach [11], in which always-on macrocells aredeployed for basic coverage and micro/picocellsare used for capacity boost. Cells for capacityboost only operate when the traffic load is highin macrocells. Otherwise, they are switched offto save energy if the macrocell is able to provideenough capacity.

While the cell switch-off approach tries tomake a good balance between performance andenergy saving, it has several limitations. First,frequently switching on/off cells affects servicesin UE. Its usage should be limited to a semi-stat-ic manner. Second, switching off cells mayreduce the battery life of served UE units asthey have to connect with other cells far away.Third, if switching off a cell creates uncoveredareas, remaining active cells need to increasetheir power to cover this area. This may neutral-ize the energy saving gain.

Layered Structure — We propose the layered struc-ture approach [12] to further improve EE ofwireless access networks. The layered structureis a combination of different systems/networks toserve same mobile devices. Layers are allowed touse different RATs. Normally , a wireless widearea network (WWAN) is deployed in one layer,and wireless local area networks (WLANs) areused in other layers. Assuming a two-layer struc-ture where macrocells form one layer and femto-cells another, as femtocells are usually deployedmuch closer to UE, less transmission energy isneeded to maintain equal QoS. It is reasonablefor the UE to hand over to a femtocell whenfeasible for energy saving. Moreover, a macro-cell RBS can further reduce its energy consump-

In general, frequencydomain solutions

have less impact onUE. However, due tothe aforementionedconstraints, the effi-ciency of frequencydomain solutions is

limited. They arenormally combinedwith energy saving

methods in otherdomains.



tion by offloading the traffic load to femtocells,and then applying macrocell RBS energy savingtechniques, for the components of a macrocellRBS consume much more energy than the coun-terparts of a femtocell RBS.

The layered structure is used to improvecapacity, coverage, and EE of the network. It isan extension of HCS. Different from HCS, it hasno constraint on deployment but relies on closecoordination between layers to achieve coexis-tence and energy saving. The layered structureapproach uses flexible architecture to optimizethe use of energy, spectrum and other resourcescross systems. It dynamically allocates the trafficload among different layers of the system andreconfigures different layers to meet servicerequirements and energy saving goals. Trafficoffloading algorithms and mobility managementare keys to achieve energy saving in the pro-posed architecture.

HYBRID SOLUTIONSHybrid solutions combine solutions in differentdomains to adapt energy consumption of anRBS in different traffic conditions. For instance,to maximize the energy saving gain under verylow downlink traffic conditions, an RBS can beconfigured to use single carrier under the carrieraggregation case, a single antenna, 1.4 MHzinstead of 20 MHz bandwidth, and the maximumnumber of MBSFN subframes in a frame. Pre-liminary studies have shown it provides signifi-cant improvement against a standalone solution.The challenge of hybrid solutions is the process-ing/interruption time and signaling for systemreconfiguration, as well as avoidance of theimpact on UE performance. Reducing the cellbandwidth and changing the antenna number

introduce system information update time andreconfiguration time in an order of 10 ms; chang-ing the carrier frequency will force the UE tohand over to another cell and then back to thenew carrier. It may take a long time for a systemreconfiguration to reach a stable cell workingstatus. Therefore, hybrid solutions are recom-mended only in semi-static traffic conditions.

PERFORMANCE COMPARISON

Performance of different network energy savingapproaches discussed in 3GPP RAN WG1 hasbeen actively studied [8, 13]. The preliminaryresults are shown in this section. The energy sav-ing gains of different energy saving approachesunder a given daily traffic pattern are shown inFig. 5. The daily traffic pattern is assumed inFig. 6, which includes 7 h low load time and 2 hidle time. It should be noted that different trafficpatterns lead to different performance results.

The energy saving gains of differentapproaches is compared with the full load casewhere no described energy saving technique isapplied. In those approaches the hybrid solutiondynamically configures the cell bandwidth, carri-er number, antenna number, as well as theMBSFN subframe number in a frame accordingto the load condition of the RBS [13].

Seen from Fig. 5, the energy saving approach-es for no load scenarios, which are extended cellDTX and MBSFN for no load, achieve energysaving gain less than 8 percent. This is becausethe idle time only occupies a very small fractionof time during a day. The energy savingapproaches working for the low load scenariosprovide better energy saving performance thanthose only working in the no load scenarios.Among three low load approaches, MBSFN forlow load shows highest performance. The band-width reduction solution outperforms the anten-na number reduction solution. A better energysaving gain can be achieved by the hybrid solu-tion.

RESEARCH CHALLENGES

Fundamental research problems remain in thenetwork energy saving research of green wirelesscommunications. First of all, the study of EE ingreen wireless communications has to be kept inmind a holistic view, which covers probably allaspects in the ecosystem of communications. It isfor several reasons. First, in additional to theenergy consumed in the use phase of a system,the embodied energy, which is the energy usedto manufacture telecom equipment, also playsan important role in the evaluation of any EEsolution. The introduction of any new architec-ture and device for EE improvement shouldconsider the total energy consumed in the lifecycle of the system. Second, the optimization ofEE at one point of the system may lead to sub-optimal results at other points. For instance, theapplication of a complex signal processing algo-rithm may reduce the transmission energy forthe same amount of data, but drain more powerfor signal processing and cooling. It is necessaryto consider the EE solution from the system per-spective. Third, for a communication system the

Figure 5. Relative energy consumption of different network energy saving techniques.

Network energy saving solutions and reference model

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4. MBSFN for low load5. Extended cell DTX6. MBSFN for idle cell

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improvement of EE should not compromise therequired QoS. A good trade-off is neededbetween performance and energy saving gain.For instance, the aforementioned network ener-gy saving approaches shall avoid any severeimpact on the user experience of UE. A holisticapproach is needed for comprehensive under-standing of the whole system, which further ren-ders challenges on energy consumptionmodeling, use of EE metrics, and system-levelEE design.

An EE solution is developed based on certainenergy consumption model. A good energy con-sumption model captures key variables of a sys-tem regarding energy consumption whileproviding sufficient abstraction. The challengeon modeling energy consumption of a system isthat energy consumption of telecom equipmentis implementation-dependent and load-depen-dent. Conforming to the same standard, differ-ent systems offering similar capacity performancemay show significant different energy consump-tion features. Consequently, a network energysaving solution based on a common model maybe far from achieving best energy saving gain fora specific system. It then requires special atten-tion on the energy consumption model beforeapplied it in a specific network energy savingstudy.

The EE metric is normally defined as a per-formance per unit of energy, and for networkenergy saving the performance usually refers tothroughput. They remain important EE metricsfor EE study. For instance, the metric of bit perjoule is the widely used EE metric which pro-vides the absolute comparison of EE among dif-ferent systems. However, the delivery capacity ofa system is used to provision services. Conven-tional EE metrics like bit/joule are insufficient tocapture EE from the service perspective. A ser-vice provisioned by multicast with a low bit/joulefigure may still outperform that by unicast with ahigh bit/joule figure on EE. Moreover, QoS isnormally not considered in the EE metric. Fornew EE architecture design and cooperative ser-vice development for EE, it is required to evalu-ate EE from a new angle concerning services.New EE metrics are demanded.

The main challenge of the system-level EEdesign lies in the EE improvement of the wholesystem/network through load balancing, systemreconfiguration, multi-domain scheduling, andcross layer adaptation. Given service require-ments, the EE problem at the system level canbe modeled as a joint optimization problemwhich takes into account resource allocation intime, frequency and spatial domain. Jointscheduling algorithms enabled by cooperationacross multiple RBSs are expected.

One of the most promising ways to improvesystem-level EE of wireless systems may lie incognitive approaches, in which learning is usedfor better adaption [14]. Cognitive approachescan be used at the spectrum level for spectrumcoexistence and interference management. Theuse of beamforming through multiple-input mul-tiple-output (MIMO) antennas, powered byintelligent adaptive techniques, has great poten-tial to mitigate interference and save energy.Cognitive approaches can also be applied at the

network layer to integrate heterogeneous net-works and treat EE as one of the primary opti-mization targets to provision service acrossmultiple networks.

CONCLUSION

This article provides an overview of energy con-sumption problems in wireless access networksand describes network energy saving techniquesproposed for the LTE system. It is identifiedthat the common energy consumption problemin an RBS of a wireless access system is theenergy scaling traffic load problem. This prob-lem can be tackled by solutions from the time,frequency, and spatial domains. As most solu-tions only focus on a single RBS, we believe themost promising solutions are those that applyhybrid techniques cross multiple systems/net-works. The energy saving problem cross multiplesystems/networks is less understood. Moreefforts are needed from the modeling to specificsolutions. As wireless access networks experienceexponential growth worldwide, it is important tomake EE a high priority in the design and devel-opment of wireless access networks.

ACKNOWLEDGMENTThe work from the authors of VTT is supportedby the JADE project, which is partially fundedby the Finnish Funding Agency for Technologyand Innovation under grant DN40474/09.

Yang’s work is partially supported by theNational Natural Science Foundation of China(NSFC) under grant 60902041, and by the Min-istry of Science and Technology (MOST) ofChina under grants 2009DFB13080 and2010DFB10410.

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Figure 6. An example of the daily downlink traffic load pattern of an RBS.

Time (hour)2 4 6 8 10 12 14 16 18

Low Idle Low

Low

Busy

20 220

20%Rela

tive

tra

ffic

load

40%

60%

80%

100%



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BIOGRAPHIESTAO CHEN [S’05, M’10] ([email protected]) received his B.E.degree from Beijing University of Posts and Telecommuni-cations, China, in 1996, and Ph.D. degree from Universityof Trento, Italy, in 2007, both in telecommunications engi-neering. Since 2008, he has been with VTT TechnicalResearch Center of Finland, working as senior researcherand project manager. From 2003 to 2007 he worked as aresearcher in CREATE-NET, Italy. From 1996 to 2003, hewas an engineer in a national research institute at China.His research interests include dynamic spectrum access,energy efficiency of heterogeneous wireless networks,cooperative communications, and wireless networking.

YANG YANG ([email protected]) is currently vice direc-tor at Shanghai Research Center for Wireless Communica-tions (WiCO), SIMIT, Chinese Academy of Sciences. Prior tothat, he served the Chinese University of Hong Kong,China, and Brunel University and University College London(UCL) in the United Kingdom as an assistant professor, lec-

turer, and senior lecturer, respectively. His research inter-ests include wireless ad hoc and sensor networks, wirelessmesh networks, 4G mobile systems, and cooperative com-munications.

HONGGANG ZHANG ([email protected]) is a fullprofessor at the Department of ISEE, as well as co-directorof the York-Zhejiang Lab for Cognitive Radio and GreenCommunications, Zhejiang University, China. From October1999 to March 2002, he was with the TelecommunicationsAdvancement Organization (TAO) of Japan as a TAOResearch Fellow. From April 2002 to November 2002 hewas at the TOYOTA IT Center. From December 2002 toAugust 2004 he was with the UWB Research Consortium,the National Institute of Information and CommunicationsTechnology (NICT) of Japan. He was the principal authorand contributor for proposing DS-UWB in the IEEE 802.15WPAN standardization task group. From September 2004to February 2008 he was with CREATE-NET, where he ledits wireless group in participating in a number of EuropeanFP6 & FP7 projects (EUWB, PULSERS 2). He was Co-Chair ofthe IEEE GLOBECOM 2008 Symposium on Selected Areas inCommunications. He is an Honorary Visiting Professor ofthe University of York, United Kingdom. He serves as Chairof the Technical Committee on Cognitive Networks (TCCN)of the IEEE Communications Society.

HAESIK KIM ([email protected]) received his Ph.D. degree incommunication systems from Lancaster University, UnitedKingdom. He is currently a senior scientist at the VTT Tech-nical Research Centre of Finland, and is involved in cogni-tive radio and network projects. From 2008 to 2009 hewas with NEC Laboratory Europe where he carried outWiMAX projects. From 2002 to 2006 he was with SamsungAdvanced Institute of Technology where he focused onUWB and SDR projects.

KARI VEIKKO HORNEMAN ([email protected]) receivedhis M.Sc.E.E. degree in 1980 from the University of Oulu,Finland. He is currently with Nokia Siemens Networks, Oulu,where he is working as a program manager for researchprograms. His current work is related to spectrum and ener-gy efficiency for heterogeneous networks, cognitive radios,and relay networks, mainly for LTE and LTE-A. In the pasthe has worked on channel estimation, interference cancella-tion, and suppression for WCDMA, and general signal pro-cessing implementations for transmission systems.


Network Energy Saving Technologies for Green Wireless Access Networks

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