Design of an Energy Efficient Future Base Station with Large-Scale Antenna System

17 Pages·2016·1.2 MB·English

energies
Article
Design of an Energy Efficient Future Base Station
with Large-Scale Antenna System
ByungMooLee1andYoungokKim2,*
1 SchoolofIntelligentMechatronicEngineering,SejongUniversity,Seoul05006,Korea;[email protected]
2 DepartmentofElectronicEngineering,KwangwoonUniversity,Seoul01897,Korea
* Correspondence:[email protected];Tel.:[phone]
AcademicEditor:K.T.Chau
Received:6October2016;Accepted:12December2016;Published:17December2016
Abstract: Duetothecontinuousincreaseindatademandedbyend-users,anenergy-efficientbase
station(BS)isavitaltopicofinterestthatwouldnotonlyresultinasubstantialeconomicimpacton
serviceproviders,butwouldalsoreducethecarbonfootprintofoperatinganetwork. Inthisregard,
weproposethestructureandsystematicoperationofaBSwithalarge-scale(LS)antennasystem
thatcanincreasetheenergyefficiency(EE)ofcellularsystems. TheproposedBSstructureincludes
variouspower-relatedunits,suchasacentralmanagementapparatus,powercontroller,EEcalculator,
radiosite-dependentparameterspace(RSD-PS)anddeterminer. Withtheinformationprovidedfrom
eachunit,thedecisionunitdetermineshowtoadjusteachcomponentoftheBSinordertomaximize
theEE.ExtensivesimulationsshowthattheproposedBSimprovestheEEperformancebyabout
83.05%relativetothereferenceBS.
Keywords: energyefficiency(EE);large-scale(LS)antennasystem;basestation(BS)
1. Introduction
Communicationtechnologiesthatcanincreasechannelcapacity,aswellasenergyefficiency(EE)
wouldbeakeyfactorforfuturewirelesssystems. AnincreaseinEEisveryimportantbecausethe
continuousincreaseindatademandedbyend-usersresultsinahighcostbothfromanenvironmental
andtechnologicalperspective. Itiswellknownthatbasestations(BS)consumearound60%–80%of
powerconsumptionincellularnetworks[1–3]. Thus,reducingthepowerconsumptionofaBSisquite
importanttoreducetheoperationalcosts,aswellasthecarbonfootprint. Forthisreason,researchers
haveactivelyinvestigatedthisproblem[1,2,4–15].MostworkhasconcentratedonimplementingtheBS
on/offtechnique,whichmeansthattheBSisturnedoffwhenthereisnonearbytraffic[1,2,9,10,12,14],
aswellasonconductingtheoreticalhigh-levelanalysesandoptimizationstoreducetheBSpower
consumption[7,8,11,13]. However,theBSon/offtechniqueisonlybeneficialforanemptynetwork,
whichrarelyhappensinactualnetworks. Furthermore, therecouldbemanyrealimplementation
obstaclesfortheoretical,high-leveloptimizationtechniques.
Inthispaper,ratherthanpresentingaBSon/offmechanismorsolvingthetheoreticaloptimization
problem,wefocusonmorepracticalimplementationaspectstoimprovetheEEofcellularsystems.
Weproposeafutureenergy-efficientBSstructureanditsrelatedoperationusingarealisticpowermodel
forrealimplementation. Duetothelimitedspectrumresources,itisalsoinevitableforthenumber
oftransmitter(TX)antennasintheBStocontinuouslyincrease[11]. Thus,weassumethatafuture
BShasalargenumberofTXantennas,thatisalarge-scale(LS)antennasystemorLSmultiple-input
multiple-output(MIMO)[16–18]. Actually,inthecaseofaBSwithLS-MIMO,theresourceallocation
problemsareeasiertosolveifthechannelpropertiesprovidedbyLS-MIMOsystemsareexploited
smartly[19,20].
Energies2016,9,1083;doi:10.3390/en9121083 www.mdpi.com/journal/energies
Energies2016,9,1083 2of17
The proposed energy-efficient BS consists of five main components: a central management
apparatus, power controller, EE calculator, radio site-dependent parameter space (RSD-PS) and
determiner. Thecentralmanagementapparatusmanagestheappropriatepowerconsumptionofeach
BSlocatedinapre-definedrange. Thepowercontrollercontrolsthepowercontrolofeachrelated
device. TheEEcalculator,whichoperatesbasedonthepowerconsumptionanddatarateestimator,
providesthepowercontrolmetric. TheRSD-PSaccumulatesinformationandsupportstheincrease
in EE according to past operation information. The determiner for each decision unit decides the
operationpointsofthepower-relateddevicesforapre-definedtimeduration. Eachcomponentcan
alsobedividedintoseveralsub-components. Withthesecomponents,weshowhowtosystematically
increasetheEEoftheproposedfutureBS.TheBScouldalsobeusedasahubforaLSsensorsystem
forasmartcityorsuch.
Inwhatfollows,weintroducethesystemmodelinSection2.InSection3,wepresenttheproposed
BSstructureandthemethodusedtosystematicallyincreasetheEEoftheBS.InSection4,wepresent
numericalresultsbasedonareferencefutureBSmodel,showingtheeffectivenessoftheproposed
structureandmethod. Finally,theconclusionsaredrawninSection5.
2. SystemModel
ThissectiondescribesthepowerconsumptionmodelandtheLS-MIMOmodel,whicharethe
coremodelsusedintheperformanceanalysisoftheproposedBS.
2.1. PowerConsumptionModel
Modeling the BS power consumption is an important problem to measure the EE. A typical
BS is composed of many power consumption components, including a supply, cooling, baseband
(BB),radiofrequency(RF),poweramplifier(PA),lossfactorsforDC-DC,feedingcable,andsoon[5].
Somestudieshaveroughlydividedthisintostaticpoweranddynamicpower[21]. Itisdifficultto
estimatehowtechnologywouldevolve,anddesigninganexactmodelisbeyondthescopeofthis
paper. However,arealisticmodelcouldbehelpfulinanalyzingtheproposedmethods. Inthispaper,
wedefinethetotalpowerP foratractablepowerconsumptionmodelthatincludessomeofthe
total
importantBSpowerconsumptioncomponents. WedefineP as:
total
P = P +P (1)
total PA Cir
whereP isthePApowerconsumptionandP isthecircuitpowerconsumptionexceptforthePA
PA Cir
powerconsumption,includingtheBBpowerconsumption,P ,andRFfront-endpowerconsumption,
BB
P . Inthismodel,sincemaximumradiationpowerislimitedregardlessofthenumberofTXantennas
RF
N,weshouldkeepinmindthat P canbereducedwiththehelpofabeamformingeffect,while
t PA
P increases as N increases. We describe below each of the power consumption components in
Cir t
furtherdetail.
2.1.1. PowerAmplifier
ThePAisoneofthemostpower-hungrydevicesinthecurrentBS.Currentcellularstandards,
i.e., 3GPP-LTE-A,IEEE802.16(e/m), useorthogonalfrequencydivisionmultiplexing(OFDM)for
downlinktransmission. TheOFDMhasaveryhighpeak-to-averagepowerratio(PAPR),andthis
significantlyreducesthePAefficiency[22]. Ifweassumea10-MHzBWwitha1024IFFTsize,withless
thana1%distortionprobabilityorcomplementarycumulativedistributionfunction(CCDF),PAPRis
knowntobehigherthan11dB.Basedonthis,wechooseaninput-back-off(IBO)=11dB[22]. Wealso
simply assume the use of the maximum efficiency of the Class-B amplifier (78.5%). Then, the PA
efficiency,η(%),canberepresentedas[23,24]:
π
η(%) = (2)
4p
Energies2016,9,1083 3of17
√
wherethe pisthe IBO. Dependingontheparametersthatwementioned,thePAefficiencycanbe
η =22%. However,variousadvancedtechnologiescanbeappliedtoobtainanincreasebymorethan
that,andthus,wereasonablychooseη =25%. Thesimplerelationbetweenthetransmissionpower
P andP canberepresentedas:
tx PA
P = ηP (3)
tx PA
It is possible for the TX power to be reduced if we increase the N, due to the channel gain
t
increment. Note that we assume the system does not adopt any predistortion and/or PAPR
reductiontechniques.
2.1.2. CircuitsPowerConsumption
Thecircuitpowerconsumptioncanalsobedividedasfollows:
P = P +N P (4)
Cir BB t RF
Eachparameterisafunctionofbandwidth,B,andweuseB =10MHz. P canalsobedividedas:
RF
P = P +P +P (5)
RF DAC m filt
where P is the digital-to-analog converter (DAC) power consumption, P is the mixer power
DAC m
consumptionandP istheTXfilterpowerconsumption[25].
filt
In this paper, we assume that we can adjust the RF power consumption. It would then be
obvious for fine DAC/filtering to be difficult if we reduce the RF power consumption. Based on
this assumption, we propose the RF power consumption model shown in Figure 1. This model
indicatesthattheperformanceoftheRFfront-endcircuitsdependsonthepowerconsumptionof
those. Forexample,assumingwecanadjusttheRFpowerconsumptionfrom0.1to1W,whenthe
RFpowerconsumption=0.1W,thenoisefromcoarseprocessingistoohigh,andSNR ,thesignal
RF
toRFnoiseratioduetocoarseprocessing,is0dB,i.e.,thenoiselevelandsignallevelarethesame.
Meanwhile, SNR is20dB,whenRFpowerconsumption=0.7W,andarelativeleveloffineRF
RF
processingispossible. RegardingtheBBpowerconsumption, P ,wealreadymentionedthatwe
BB
assumeafutureBStohaveLS-MIMOcapability. Withthatinmind,H.YangandT.Marzettapresented
anLS-MIMOBBcomputationmodel,χ(Gflops),whichisdenotedasfollows[26–28]:
(T B) (T B)
χ(Gflop) = N × u ×log (T B)+N × d ×τ ×log (τ )
t T 2 u t T r 2 r
s sl
(T B) (T B)
+N ×K×(T−τ )× d +M×K2× d (6)
t r
T T
sl sl
whereτ isthelengthinthesamplesoftheuplinkpilotsequences,whichareusedtoacquirechannel
r
stateinformation(CSI),andadescriptionofeachparameterisshowninTable1.Wetooktheparameters
from[29]andfromacurrentLTEsystem[30]. ThefirstpartofEquation(6)istooperatetheFFT/IFFT
operation; the second part is to implement precoding/decoding; the third part is to correlate the
pilot signals with pilot sequences; and the last part is to have the additional pseudo inverse for
zero-forcing(ZF).
TherelationshipbetweenP andχ(Gflops)canberepresentedas:
BB
χ(Gflops)
P = (7)
BB (cid:36)(Gflops/W)
where(cid:36)isthevery-large-scaleintegration(VLSI)processingefficiency.
WeassumeT = T ,ashortguardinterval(GI)andfastpilotcorrelation. Threepilotsymbols
g d
are dedicated to one slot for the channel estimation [29]. Note that this model does not include a
Energies2016,9,1083 4of17
channelcodingpart,andthelastpartofEquation(6)becomeszero,whenweusematchedfiltering
(MF)precoding.
1 40
el
v
e
L
se B)
ed Noi0.5 20 R (dRF
z N
ali S
m
or
N
0 0
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
RF Power Consumption per N
t
Figure1.Radiofrequency(RF)powerconsumptionmodel.
Table1.Baseband(BB)powerconsumptionparameters.GI:guardinterval.
Parameters Description PowerConsumption
B Bandwidth 10MHz
T Slotlength 0.5ms
sl
Tp Pilotlengthinoneslot 0.214ms
Ts Symbolduration 71.4µs
Tg GI 4.7µs
Tu SymbolwithoutGI 66.7µs
T Delayspread 4.7µs
d
2.2. Large-ScaleMultiple-InputMultiple-OutputModel
In this subsection, we summarize the LS-MIMO model since the LS-MIMO would be a very
importantcharacteristicofafutureBS.AnLS-MIMOisanantennasystemwithalargenumberof
TXantennas. ItwasfirstintroducedbyMarzetta[29],andafterthat,muchresearchhasbeencarried
out [19,20,28]. Due to its desirable improvements in throughput (TP) and EE, it has already been
discussed by the important standardization body, i.e., the the 3rd Generation Partnership Project
(3GPP), as one of the core technologies for 5 G. In 3GPP, the LS-MIMO is usually referred to as
full-dimension MIMO (FD-MIMO). Therefore, it is unquestionable for the LS-MIMO to be a key
technologyforfutureBS.
TheantennastructureofaBSequippedwithLS-MIMOcouldbeofvariousshapesdependingon
theimplementation. Oneexampleofahigh-levelconceptualfigureofanLS-MIMOsystemisshown
inFigure2.
EachantennahasitsownRFcomponent,asshowninFigure3,andthestructureinFigures2and3
canbeusedtogenerateaverysharpbeam.Thedesignercanchoosetoputmoreantennasinthevertical
directionorhorizontaldirection. Ifweputmoreantennasintheverticaldirection,theresolutionofthe
verticalbeamseparationisverygood,andthus,userswhoarelocatedoneachfloorofabuildingcan
benefit. Ifweputmoreantennasinthehorizontaldirection,itcanprovideahorizontalseparation
effect,andthus,userslocatedindifferenthorizontalanglescanbenefit.
Energies2016,9,1083 5of17
Figure2.Anexampleofahighlevelconceptualfigureofalarge-scalemultiple-inputmultiple-output
(LS-MIMO)system.
Antenna
RF component
Figure3.AnimplementationexampleoftheantennaandRFinanLS-MIMOsystem.
However,therearesomeobstaclestorealizeLS-MIMO.First,theantennaspacingshouldbeat
leastλ/2,whichmeansthatitrequiresaquitelargespaceforinstallationandusewithcellularbands.
Eventhoughhigherfrequencybandscouldbeagoodoption,thepoorchannelconditionshouldbe
overcame. Second,itrequiresmanyRFchains,whichareveryexpensive. Goodantennaselection
algorithmscanbeveryhelpfultoreducethenumberofRFchains[16]. Thus,implementingLS-MIMO
withalowcomplexityandcostisabigresearchtopic.
TointroducetheoperationoftheLS-MIMOsystem,letusthinkofasingleisolatedcellwithone
BS and Kuser terminals. The BS has N TX antennas, and each user terminal has one RX antenna.
t
Thereceivedsignalvectorattheterminalscanberepresentedasfollows:
√
y = P Hs+n (8)
tx
where y is the K×1 received signal vector for K user terminals, P is the total TX power for the
tx
downlink,HistheK×N channelmatrixbetweenN BSantennasandKterminals,sistheN ×1TX
t t t
Energies2016,9,1083 6of17
signalvectorandnistheK×1noise(AWGN)vectorattheterminals. Theelementofthechannel
matrixbetweenthem-thBSantennaandthek-thterminal,h canbedecomposedas:
km
h = g ·χ (9)
km km k
whereg isthezero-meanandunitvariancei.i.d. Rayleighfadingchannelcoefficientandχ isthe
km k
path loss component. We only consider the narrowband signal, since the OFDM can successfully
changethewidebandsignalintoanarrowbandsignal. TheTXisassumedtohaveperfectCSI.Toshow
thechannelhardeningeffectwithLS-MIMO,itisusuallyrequiredforN >10K,whichmeansthat
t
thenumberofTXantennasintheBSshouldbemuchmorethanthenumberofusers[16].
2.2.1. PrecodingMethod
PrecodingisanMIMOTXsignalprocessingmethodthatreducestheinterferenceamongtheusers.
Since N wouldbeverylargeinafutureBSequippedwithLS-MIMO,linearprecodingistractable
t
forrealsystems. ZFandregularizedzero-forcing(RZF)arewellknownaseffectivelinearprecoding
techniques[31,32]. Furthermore, T.Marzettasuggestedanevensimplerprecodingtechnique, MF
precoding[29]. MFprecodingisonlyeffectiveforLS-MIMO,whileZF/RZFprecodingisalsouseful
fortraditionalMIMO.TherelationbetweentheTXsignalvector,s,andthemassagesignalvector,x,is
expressedasfollows:
s = ζFx (10)
whereζ istheTXpowernormalizationfactorandFistheN ×Kprecodingmatrix.
t
Then,(8)canberewrittenas:
√
y = P HζFx+n (11)
tx
AllthreeprecodingmatricesarepresentedinTable2.
Table 2. The precoding matrices of matched filtering (MF), zero-forcing (ZF) and regularized
zero-forcing(RZF).
MF ZF RZF
F N−1HH HH(HHH)−1 HH(HHH+νI )−1
t K
Inthetable,superscript“H(cid:48)(cid:48) denotestheconjugatetranspose,(·)−1istheinverseoperatorandI
K
istheK×K identitymatrix. RZFprecodingcanbethesameasZFand/orminimummeansquare
error(MMSE)precodingifwechooseν =0and/orν = KN0 .
NtPtx
As N grows without bounds, the autocorrelation of the channel vectors can be simplified as
t
follows[29]:
HHH → NI (12)
t K
Simply,wecall(12)anLS-MIMOchannelcharacteristic. Ifweapply(12)totheMMSEandtheZF,
theMMSEandtheZFcanbesimplifiedas[16]:
KN
HH(HHH+ 0 I )−1 ≈ HH(HHH)−1 → N−1HH (13)
N P K t
t tx
ThismeansthatwithanexcessivenumberofTXantennaswithalimitednumberofRXantennas,
allrepresentativelinearprecodingtechniquesshowsimilarperformance. ZFiswellknowntobenear
optimalinaregionwithveryhighSNR.Ifweconsiderthecomplexityofthenonlinearprecoding
techniquesandhigheffectivesignal-to-interferenceplusnoiseratio(SINR)oftheLS-MIMOsystems,
linearprecodingwouldshowsufficientperformancewithlowcomplexity.
Energies2016,9,1083 7of17
Now,letusdeterminethenormalizationfactorζ. Thenormalizationfactorshouldbedetermined
suchthatthetotaltransmitpowerbecomesP . Thismeans:
tx
(cid:107)ζFx(cid:107)2 =1 (14)
F
where(cid:107)(cid:107) standsfortheFrobeniusnorm.
F
SinceFandxareindependent,andwealreadychoosetheaveragepowerofthesignalconstellation
inunity,ζ canberepresentedas[16]:
(cid:114)
N
ζ ≈ t (15)
K
TheZFandMMSEprecodingshowaverysimilarperformance,evenwitharelativelypractical
numberofLSTXantennas(i.e., N ≈ 10K).Forthisreason,weonlyuseMFandZFasprecoding
t
techniquesinthispaper.
2.2.2. ThroughputandEnergyEfficiency
TheTPandEEaretwoimportantmetricsthatcanbeusedtoconductaperformanceanalysis.
Basedontheanalysisfromprevioussubsections,thesymbolreceivedbythek-thuserisgivenas
follows[29]:
(cid:114) (cid:114)
y = PtxNth f x +n + PtxNt ∑h f x (16)
k K k k k k K k l l
l(cid:54)=k
whereh isthe1×N channelvectorforthei-thuserandf istheN ×1precodingvectorforthei-th
i t i t
user. Thelasttermof(16)isinter-userinterference(IUI).Then,theeffectiveSINRforuserk,γ ,canbe
k
representedasfollows[4]:
PtxNt|h f |2
γ = K k k (17)
k PtxNt|∑ h f |2+N B
K l(cid:54)=k k l 0
whereN BisthenoisepowerinthegivenbandwidthB.
0
IfweincreasethenumberofTXantennasorreducethenumberofusers,itisobviousthatwe
cangetbetterchannelgainand/oraneffectiveSINR.However,weshouldkeepinmindthat,inthe
practicalnumberofTXantennas,MFprecodingdoesnotremovetheIUIcompletely.
Basedon(17),wecandefineTPasfollows:
(cid:34) (cid:32) (cid:33)(cid:35)
TP = αB× ∑K E log 1+ PtxKNt|hkfk|2 (18)
2 PtxNt|∑ h f |2+N B
k=1 K l(cid:54)=k k l 0
whereα = (cid:16)Tsl−Tp(cid:17)×(cid:16)Tu(cid:17)isthescalingfactorforthepilotoverheadandguardinterval[29].
Tsl Ts
EEcanbedefinedas:
EE = TP/P (19)
total
Wewilluse(19)asthemetricfortheperformanceanalysisinthefollowingsections.
3. Energy-EfficientBSStructureandRelatedOperation
ToachieveahighEEfortheBS,itisessentialtocontrolsomeoftheimportantTXparameters
there. WecandividethemainBSpowerconsumptioncomponentsinPA,RF(exceptPA)andBBand
makeouteachcomponenttobeapower-adjustingcomponent. ThePAisthemostpower-hungry
device in the current BS, but this could change depending on the situation of a future BS. Since a
futureBScouldhavealargeamountofRFchainsconnectedtoeachantenna,itisalsopossiblefor
theRFchaintoconsumemorepowerthanthePA.IncontrasttothePA,whichcanreducethepower
consumptionbyusingabeamformingeffect,therearenodistinctsourcestoreducetheRFchainpower
consumption. TheBBmayconsumelesspowerwhencomparedtothePAandRF.However,itisbetter
Energies2016,9,1083 8of17
toincludeitasoneoftheadjustableparameterstoenhancetheEE.Thethreemaincomponentscanbe
controlledasshowninFigure4.
User 1
RF PA
 RF PA User 2
Baseband   User 3

RF PA
User K
Power Control Unit
Figure4.Thehighlevelconceptualfigureoftheenergy-efficientfuturebasestation(BS).
Anenergy-efficientfutureBSisquiteobviouslyafeedbacksystem. Itmainlyreceivesinformation
of the power consumption from the BS TX unit and information regarding the data rate from the
userterminals. Asshowninthefigure,thepowercontrolunitcontrolseachcomponentbasedonthe
measuredEEparameters. TheproposedBSmeasuresthedatarate,andifitisnotinasatisfactory
range,itprovidesaninputtopowertheadjustableunittoincreasethepowerconsumptionofsomeof
thecomponents. Then,basedonthepoweradjustmentofeachcomponent,thedatarateestimation
unitmeasuresthedatarateagainandchecksifitisinthesatisfactoryrange,andsoon. Ifthepower
consumptionistoohighoverapre-definedthreshold, thenthedataratecouldalsobereducedto
obtainsatisfactoryEEperformance.
Basedonthehigh-levelconceptofafutureBS,thedetailedblockdiagramoftheproposedBS
structureisdescribedinFigure5.
Central BS
Management Unit
Radio Site Dependent
User Parameter Space (RSD-PS)
Terminal
EE RSD-PS
Data rate RSD-PS
BS TX/RX
Power Consumption RSD-PS
Power control unit
Power consumption estimation unit
Data rate estimation unit
Decision Unit
Energy Efficiency (EE) (bps/W)
Computation unit
Figure5.BlockdiagramoftheproposedBSstructure.
Energies2016,9,1083 9of17
First,letusobservetwounits,thepowerconsumptionestimationunitandthedatarateestimation
unit, which are tightly connected with the fundamental TX/RXunit of the BS. The BS provides
information for the units based on feedback from self-measurement and user terminals, then EE
(bps/W)canbederivedbasedontheresults. Allinformation(powerconsumption,datarate,EE)is
giventothedecisionunit,whichcanthendecideeachcomponent’spowerconsumption,i.e.,PA,RF
andBB.ThedecisionunitprovidesfeedbackonthedecisiontothefundamentalTX/RXunitoftheBS.
Then,theBSperformspowercontrolbasedonthefeedbackinformation.
Therearethreemorecomponentsinthisstructure,asshowninthefigure. Thefirstoneisthe
centralBSmanagementunit. Thisapparatuscanbeusedformulti-BSpowercontrol/optimization.
The central BS management unit monitors all nearby BSs and adaptively allocates the allowable
maximumpowerforeachBS.Then,eachBSonlyallocatespowerforeachcomponentbasedonthe
totalallowablepowerconsumptioncriterion.Thesecondoneistheuserterminal.Inparticular,thedata
ratecanbeeasilymeasuredwithauserterminal. Furthermore,itisbeneficialfortheuserterminal
togivefeedbackregardingthecurrentchannelcondition. ThelastoneistheRSD-SP.TheRSD-SP
istheapparatusthataccumulatesthehistoryofoptimumBSoperation,andsupportsthedecision
unittodeterminetheoperatingpointsofBSbasedontheaccumulatedhistorywhenevernecessary.
For example, RSD-PSmonitors theBS operation, suchas thelevel ofradiation power, the levelof
theresolutionoftheRFchain,thelevelofBBprocessingbasedonoperatingparameters,suchasthe
numberofTXantennas,thenumberofusers,systembandwidth,thechannelcondition,andsoon.
Afterhavingaccumulatedenough,theRSD-PScanassisttomaintainthehighEEBSbyprovidingthe
historyofoptimumEEoperationpointsbasedonoperationparameters. TheBScangetevenhigher
energy savings by skipping the real calculation of operation points for some interval. The system
parametersfortheoperationofanenergy-efficientBSissummarizedinTable3.
Table3.Thesystemparametersfortheoperationofenergy-efficientBS.PA:poweramplifier.
OperationMetrics Parameters
ChannelInformation(fromTerminal)
SystemBandwidth(fromBS)
DataRate Radiationpower(fromBS)
NumberofOperatingTXantenna(fromBS)
NumberofCo-ScheduledUserTerminals(fromBS)
PApowerconsumption(fromBS)
PowerConsumption RFpowerconsumption(fromBS)
BBpowerconsumption(fromBS)
Note that the performance of the proposed power control scheme critically depends on the
thresholdofthedatarateandpowerconsumption. Thethresholdisabandwidth-limitedregimeanda
power-limitedregimeinShannon’schannelcapacity. Increasingpowerguaranteesincreasingthedata
ratesignificantlyuptothepower-limitedregimeinchannelcapacity. However,ifthesystemgoesto
thebandwidth-limitedregimeinchannelcapacity,thedatarateisnolongerincreasedsignificantly,
evenifweincreaseitwithlargeamountsofthepower.
TherearevariouswaystoadjusttheTPordatarateandEEusingthepowercontrol,asshownin
Table4. Thereisatrade-offbetweentheEEandTP.However,ifweappropriatelyallocatepowerfor
eachcomponent,itcouldbepossibletoincreasebothEEandTP,suchaswhenusingbigdata/machine
learning-basedRSD-PS.ToshowthesystematicoperationoftheproposedBS,weprovideoneexample
usingaflowchart,asshowninFigure6.
AftergatheringimportantparametersfromtheBSTXpartsanduserterminals,theproposedBS
canderivetheEEbasedonthepowerconsumptionestimationanddatarateestimation. Wesetthe
numberofiterationsfortheparameteradjustmentbetweenthedatarateandthepowerconsumption
toobtaintheexpectedperformance,aswellastoreducethecomplexity. Ifthepre-definednumber
Energies2016,9,1083 10of17
of iterations is smaller than the current number of iterations, then the iteration stops, and the BS
findstheoperationpointbasedontheinformationofthecurrentparametersandtheRSD-PS.Ifnot,
theproposedBSestimateswhetherthecurrentpowerconsumptionislargerthanthethresholdfor
thepowerconsumption. Ifthecurrentpowerconsumptionislargerthanthethreshold,theproposed
BSreducesthepowerconsumptioninappropriatewaysbyusingtheRSD-PS.Then,theproposed
BScheckstheTP.IftheTPiswithinthesatisfactoryrange,withthehelpofRSD-PS,theproposedBS
determinestheoperatingpoint. IftheTPisnotinasatisfactoryrange,theproposedBSgoestothe
loopandincreasesthepowerconsumptiontoobtainabetterTP,andsoon.
Table4.ExamplesofBSoperation.TP:throughput;EE:energyefficiency.
(1) MethodtoincreaseTPwhiledecreasingEE
(2) MethodtoincreaseEEwhiledecreasingTP
(3) MethodtomaintainEEwhileincreasingTP
(4) MethodtomaintainTPwhiledecreasingEE
(5) MethodtoincreasebothTPandEEandincreaseTPfurther
(6) MethodtodecreasebothTPandEEanddecreaseEEfurther
Start
Getting BS operation parameters
Power consumption estimation
Data rate estimation
Current EE (bps/W) computation
Yes
iteration  iteration ?
th
No
No
iteration  iteration 1 power  power th ?
Yes
Increase power consumption Reduce power consumption
Refer RSD-PS Refer RSD-PS
No
bps  bps ?
th
Yes
Refer RSD-PS
Operation point Decision
Control Power of the component
End
Figure6.ExampleofthesystematicoperationoftheproposedBS.
A proper power control algorithm should be included to reduce inter-cell interference.
Afterachievinganoperatingpoint,theBScouldoperatewiththeoperatingpointforawhile.Afterthat,
theprocesscouldbeperformedagainbecausetheoptimumpointcanchangeanytimeinadynamic
wirelessenvironment. Notethattheoperatingprocedurecanbedeterminedinvariouswaysbasedon
theproposedBSstructure.