一种简化的Turbo码并行译码方法

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ASimplifiedParallelDecodingSchemeforTurboCodes

WangLe,HuangYu,YangHongwen

WirelessCommunicationCenter,BeijingUniversityofPostsandTelecommunications,Beijing,China(100876)

Abstract

ParalleldecodingofTurbocodesisvitaltotheapplicationswithveryhighdatarates.Intheoverlappingparalleldecodingscheme,thedecodingthroughputcannotincreaselinearlywiththenumberofsegments.Aschemewherethethroughputcanincreaselinearlywasproposed,wheretheboundaryinformationofeachiterationisstoredtobetheinitialconditioninnextiteration.Inthispaper,wehavesimplifiedtheschemebyonlystoringtheindexofthemostprobablestateoftheboundary.Withthecostofsomesmallperformanceloss,theschemecanreducelargelytheextramemoryrequiredtostoretheboundaryinformation.

Keywords: Turbocodes;MAPalgorithm;paralleldecoding

Introduction

Withtheever-increasingdemandofthedatarate,turbocodeisfacingstringentchallenges.ITUsuggeststhatthedatarateof4Gsystembeatleast100Mbps,inmobileconditions.Asthelocaloperatingclockfrequencyinhardwaresystemistypicallywithin100MHznowadays,itisreported[1]thatthethroughputofonly6.17Mbpscanbeachievedforturbocodeswithconventionalserialdecoding[2].Obviously,thedecodingalgorithmofturbocodehastobeimprovedsignificantlytosurviveinthefuturecommunicationsystems.

Thebottleneckofthethroughputliesinitsdecodingscheme.Theconvolutionalcodesistypicallyemployedastheconstituentcodes,leadingtothedecodingalgorithmemployssomerecursiveschemesbasedontrellis,suchassymbol-by-symbolMaximumAPosterioriprobability(MAP)algorithm[3].Itrequireslotsofrecursivecomputationsinbothcomponentdecoders.Moreover,thedecodingprocedureisiterative.Hence,thedecodingdelayisquitelarge.

Toreducethedecodingdelayandimprovethedecodingthroughput,theparalleldecodingmethodwasproposed[4]bydividingthewholeframeintomultiplesub-blocksanddecodingthesegmentswithabankofidenticalsub-blockMAPprocessors.Withtheparalleldecodingscheme,thethroughputcanbeimprovedbyafactorofaboutK,thenumberofsub-blockssegmented.Underthesameconditionsasmentionedpreviously,thethroughputof100MbpscanbeachievedwithK=16.

However,asaresultofthesegmentation,eachsub-blocksuffersthelostofboundaryinformation(initialconditions),whichisvitalfortheperformance.Togettheboundaryinformation,amethodwithsegmentsoverlappingisproposed[4],bycomputingsomemoreredundanttrellisstages.However,suchoverlappingsufferssomeextracomputationaldelay,andleadstolowerdecodingspeed.TheactualspeedupfactorissmallerthanK,especiallywhenKislargeandtheframelengthissmall.Anotherwaytogettheboundarydistributioninformationwasproposedin[5].Itsuggeststousetheforwardandbackwardvariablescomputedinthepreviousiterationtoprovideanapproximationtotheboundary.Simulationresultsshowthatitsperformanceisveryclosetotheserialdecodingschemein[2].Thecostofthismethodissomeadditionalmemoryneededtostoretheintermediateboundaryinformation.

Toreducethesizeoftheadditionalmemoryin[5],wesuggestthatinsteadofthewholeboundarydistributioninformation,onlytheindexofthemostprobablestatebestored.Withthissimplifiedstoragescheme,wecansavealotofmemoryatthecostofsomeacceptableperformanceloss.

Therestofthepaperisorganizedasfollows.First,section2givesabriefdescriptionofthestandardserialdecodingtoshowitsweakpointindecodingspeed.Section3showsthetwoparalleldecodingmethodsproposedin[4-5].Ourproposedschemeisgiveninsection4andsection5isthesimulationresults.Finally,section6concludesthepaper.

SerialdecodingschemeofTurbocodes

TurbocodesintroducedbyBerrouetal[2]haveanear-Shannoncapability,thusbeingveryattractivetovariousapplications.However,thelargedecodingdelayprohibitsitsapplications,especiallyforthosetimeconstraintorhighdatarateservices.

ThedecoderofTurbocodesemploysaseriallyconcatenatedstructure,whichconsistsoftwocomponentdecoders,asshowninFig.1.Thedecodingproceedsinaniterativemanner.Ineachiteration,thefirstcomponentdecoder,correspondingtothefirstcomponentencoder,deliversitscalculatedextrinsicinformation(Le1)tothe2ndcomponentdecoderafterinterleavingtoserveastheapriori

information(La2).Thenthesecondcomponentdecoderfeedbacksitsextrinsicinformation(Le2)tothefirstoneafterde-interleaving,workingasaprioriinformation(La1).xandxinFig.1are

receivedinformationbitsanditsinterleavedversion,respectively.The

y1and

y2arereceived

redundantbitsproducedbythecomponentRecursiveSystematicConvolutional(RSC)encoders,respectively.

La1x

y1

Le1

La2

x

y2

Le2

LLRs

Figure1.DecoderofTurboCodes

ThefunctionofthecomponentdecoderistocalculatetheLLRs(LogarithmofLikelihoodRatio)fortheinformationbits.ThecalculationofLLRsgenerallyemploystheMAPalgorithm[3]wheretheLLRsfortheithinformationbitofalengthNframecanbeexpressedas

i(s)i(s)i(s,1)

LLRiLog

1

i(s)i(s)i(s,0)

0

(1)

wherethesummationinnumeratoranddenominatorisoverthesetofbranchesintrellisdiagram,inwhichtheinformationbitis1or0,respectively.NotethatwearenotgoingtoexplainthedetailsoftheMAPalgorithmoritsvariants;rather,wesimplyshowtherecursivenatureinthealgorithmsthat

prohibitthedecodingspeed.Therearethreekindsofvariablesin(1).

i(s)

and

i(s)

denotethe

forwardandbackwardvariablesintheithtrellisstage,

is,d

isthebranchmetriccorresponding

thebranchwhichstartsfromstatesandtheinformationbitisd.

Thei

in(1)canbedirectlycalculatedwithchannelinputsandtheaprioriinputswithinoneclock

cycle,providedthatalltheinputsnecessaryarereadytouse.Itistherequiresrecursivecalculationasshownin(2)and(3)forbinaryRSC:

i(s)

and

i(s)

which

i(s)i1(s1)i(s1,1)i1(s0)i(s0,0),

i1,2...N1

(2)

1

1

0

0

i(s)i1(s)i1(s,1)i1(s)i1(s,0),

iN1,N2...1

(3)

wheresd

isthepreviousstatecomingtostateswiththeinputinformationbitsasd.

isthe

s

d

arrivingstateviathecurrentstateswithinputbitasd.Theinitialconditionfortherecursivecalculationis

0

0

(s)1

(s)1

s0

else

s0

(4)

(5)

0

N else

Notethattheinitialcondition(5)onlyappliesfortheRSCwhichisterminated[6].IfRSCisopen[2],theinitialconditionshouldbe

1

N(s)2m, s

(6)

where2misthenumberofthetrellisstates.ThewholeprocessisshowninFig.2.

LLRs

Figure2.theoperationflowchartforMAPalgorithm

Apparently,tocalculatei,weshouldcalculate

i1

first.Andtocalculate

N1,wehavetowait

forallpastibeenobtainedandthesituationissimilartoi.Thus,theprocessingforone

componentdecoderinoneiterationcannotbefinishedwithinNclockcycles(someextraclock

cyclesmayberequiredtoexecutesomeotheroperations).Iftheclockfrequencyis

fc,thenthedelay

forprocessingoftheMAPismorethan

Tmap

N

f

.Supposethatthemaximumiterationis

c

Imax,then

thedelayfordecodingonecodewordofturbocodeismorethanT

2T I

2NI

,leadsto

dec map

max

max

c

ainformationthroughputlessthan

RNTdec

fc

2Imax

f

.Forexample,when

fc100MHz

and

Imax8,thethroughputcannotbelargerthan6.25Mbps.Notethatwithsomeearly-stopiterationstrategy[7],theactualnumberofiterationstosuccessfullydecodeonecodewordmaybemuchless

than

Imax,butthehardwarehavetobedesignedwith

Imax.

Paralleldecodingmethods

Toreducethedecodingdelayandimproveitsthroughput,wecandividethewholecodewordintomultiplesub-blocksanddecodethemwithmultipleMAPprocessorsinparallel.However,thesegmentsinthemiddlehavenoinitialcondition[4-5].Withrandomorarbitraryinitializationas(6)willleadtoaperformancelossthatisunacceptable.Sodirectlyworkingateachsegmentfacesaproblemofhowto

initializetheforwardandbackwardvariablesattheboundaryofeachsegment.Asshownin(2),

ks

dependsonallpast

js,jk.Notethatthefarawaythejleavesk,thelesseffect

will

j(s)

haveon

k(s).Thus,tohaveagoodaccuracyforthe

k(s)

atthebeginningofeach

sub-block,weshouldstarttheprocessingof(2)earlieratjkL

withLlargeenough[4].This

isshowninFig.3.Foracertainsub-blockoflengthMlocatingfrompositionktokM1,we

startthecalculationfromkL

with

kLs

beingarbitrarilyinitializedas(6).Theposition

kL

tok1

belongstotheprevioussub-block,hencetheparallelprocessersarepartially

overlapped.Thecalculationof

k(s)

isexactlythesame.Tohaveagoodaccuracyforthe

kM1(s)

attheright-handbeginningpointofthesegment,weshouldstartfromjkM1L.

overlappingarea

kM(s)

…

kL(s)

…

k1(s)

k(s)

…

kM1(s)

Figure3.theoverlappingmethodin[4]

Therefore,toproducealltheforwardvariables

i(s)

inonecomponentdecoderwithinoneiteration,

K

thewholeprocessingofthecodewordwithKsegmentsandLoverlappingrequiresNL

clock

cyclesinsteadofN cycles,andthedecodingspeedwillbesloweddownbyafactorof N .

K NLK

LargertheLandKis,slowerthedecodingspeedwillbe.Forinstance,assumingthattheblocklengthis2298[8],ifwesegmentitinto50sub-blocks,andtheoverlappinglengthis30,thenitrequires76clockcyclestoproducealltheforwardvariables,insteadof46cycles.Hence,theMAPdecodingspeedcanonlybeimprovedby30times,farlessthanK50,whichisoriginallysupposedtobe.

Tosolvesuchproblem,amethodwithstoragefeaturewasproposedin[5].Insteadofoverlappingtechnique[4],itutilizestheforwardandbackwardvariablescomputedinthepreviousiterationtogettheboundaryinformationforeachsub-block.Forexample,forthep+1thiterationandthesame

sub-blocklocatingfromkto

kM1,thecalculationof(2)willstartatkwithinitialcondition

k1

p1s

beapproximatedwith

ps,thefinalresultsinlastiteration.ThisisshowninFig.4.

(s)

(p)

k1

k1

Thebackwardvariableisprocessedinthesameway.

(p)(s)

kM

(p)(s)

k1

(p1)(s)

k

(p1)(s)

kM1

Figure4.themethodin[5]

Comparedwiththeoverlappingmethod,suchmethodrequiresnoredundantcomputations.Hence,thedecodingspeedcanincreaselinearlywiththenumberofsegments.However,itrequiresanextra

memoryofsize2m(K1)v

tostorethefinalresultsof

ps

inlastiteration,wherevisthe

k1

k1

numberofbitsusedtoquantizetheps.

Proposedmethod

k1

Forsomeapplicationssuchassmallmobileterminals,itispreferredthatthememoryrequiredshouldbeassmallaspossible.Tokeepthefeatureofthemethodsin[5]butsavethememory,inthispaperweproposedtostoretheindexofthemostprobablestateinsteadofalltherealvaluesofintermediate

boundary(e.g.

(p)(s)inFig.4),computedinthepreviousiteration.Withthestatenumberof2m,

weonlyneedtostorembits,ratherthan2mvbits.Thismaybealargesavingifmandvislarge.

Atp+1thiteration,forthesamesub-blocklocatingfromkto

kM1,thecalculationof(2)will

startatkandtheinitialconditionissetas(inlogarithmdomain)

logp1s 0

ss*

(7)

k1

p1

else

whereisapredeterminedparameterwhichonlydependsonthenumberofiterationsandcanbe

k1

optimizedviasimulation,s*argmaxlogpsistheindexofthemostprobablestateinthe

s

previousiteration.Withthismethod,theonlythingweneedtostoredfornextiterationisrequiresmbits.

Simulationresults

s*,which

Inthissectionwewillshowtheperformanceoftheproposedmethod.Thesimulationadoptstheturbocodedefinedincdma2000[9],theinterleaverlengthischosenasN=2298,themaximumiteration

numberis

Imax8.Thenumberofsub-blockis

K20

implyingthatthehardwareMAPprocesser

consistsof20parallelprocessorsandeachprocesses

2298/20115

bits.Bothlogmapand

max-logmapdecodingalgorithmsareconsideredandFER(frameerrorrate)andBER(biterrorrate)areobserved.

Figure5.FERperformanceofcoderate=1/3

Fig.5includesfourFERperformancecurvesforcoderate1/3,usingmax-logmaporlogmapdecodingalgorithmrespectively.AtFER=0.01,formax-logmapalgorithm,theperformancelossoftheproposedmethodisabout0.07dB,comparedwiththemethodin[5].Andforlogmap,theperformancelossatFER=0.01isabout0.1dB.

Figure6.FERperformanceofcoderate=3/4

InFig.6,wecanseethatforcoderate3/4,theperformancelossislargerthanthatofcoderate1/3.AtFFR=0.01,theperformancelossisabout0.3dBforbothlogmapandmax-logmapdecodingalgorithm.WehavealsothesimulatedBERperformancewhicharenotshownhereduetolimitedspace.TheconclusionforBERperformanceisroughlythesame.

Conclusion

Inthispaper,wesimplifiedthemethodin[5],byonlystoringtheindexofthemostprobablestate,insteadofallvaluesofintermediateboundary.Theproposedschemecanreducethesizeofmemorylargely,withsomeacceptableFERorBERperformanceloss.

References

“Throughput,latencyandcomplexityestimationfortheturbodecoder,”3GPPTSGRANWG1#46,R1-062155,

Tallinn,Estonia,Aug