2026年与人工智能集成的6G网络报告（英文版）-中信科移动

6GNETWORKSINTEGRATEDWITHAI

ENDOGENOUSINTELLIGENCE·

CAPABILITYEXPOSURE·DIGITALTWIN

DTMobileCommunicationsEquipmentCo.,Ltd.

CICTMobileCommunicationTechnologyCo.,Ltd.

ZGCInstituteofUbiquitous-XInnovationandApplications

StateKeyLaboratoryofWirelessMobileCommunications（CICT）

Abstract

ThisWhitePaperprovidesasystematicexpositionofthetransformativetrendsandtechnologicalpathwaysfor6Gnetworksintegratedwithartificialintelligence(AI),andidentifiesendogenousintelligenceasthefoundationalcoreofthe6Gmobilecommunicationsystem.Inresponsetotheexponentialgrowthofemergingservicedemandsforanultimateexperience,6Gnetworksareevolvingfromtheconventionalroleasa“datapipeline”intoan“intelligentserviceengine”,therebydrivingaprofoundandall-roundtransfor-

mationinthecommunicationsdomain.

AsdetailedinthisWhitePaper,theintegrationofAIand6Gnetworkswillbringaboutfourcoretransformations:Firstistherevolutionaryevolutionofterminalforms,whichenablesintelligentagentterminalstosupplanttraditionalterminals;Secondistheintelligentinterconnectionupgradeofapplicationscenarios,whichrealizestheleapforwardfromthe“InterconnectionofEverything(IoE)”tothe“IntelligentInterconnectionofEverything(IIoE)”;theintelligentrestructuringofnetworkarchitecture,ThirdistransitioningAIfroman“externalauxiliarytool”toan“endogenousin-tegration”;theintegrateddevelopmentofservicesystems,whichmovesfroma“communication-

centric”modeltowardthe“in-depthintegrationofcommunication,sensing,computing,andintelligence”.

Baseduponthethreekeycharacteristicsofendogenousintelligence,capabilityexposure,anddigitaltwin,thisWhitePaperconstructsahierarchicaldevelopmentpathwayforAI-integrated

6Gnetworks:thenetworkelementlevelfocuseson

high-performanceandefficientdeployment,theupperlayeremphasizesmulti-taskandmulti-networkelementcollaboration,andthetoplayercentersonadvancedintelligenceempoweredbylargemodels.Coretechnologicalinnovationfocusesonthecollaborationframeworkof“largemodels+smallmodels+networkintelligentagents”.Withthreekeytechnologicalenablers—thechannelfoundationmodel,thenetworkoperationlargemodelandthenetworkintelligentagents—thereachievesaccuratealignmentbetweenthepropagationcharacteristicsofphysicalsignalsand

thecontentofhumansocialinteractions.

ThisWhitePaperalsoconductsanin-depthanalysisoftheoperationalmechanismsandkeytechnologiesunderpinningtheexposureof6GintelligentcapabilitiestoempoweremergingAI

applications,aswellashowintelligentdigitaltwin

pioneersanewparadigmofnetworkintelligence.Throughthedual-loopcollaborativemechanismof“internalclosed-loopverificationandexternalclosed-loopfeedback”,theintelligentdigitaltwinsystemprovidesasecureverificationenvironmentforvalidatingAIstrategiesandacceleratestheadvancementofnetworkintelligence.LeveragingthecharacteristicsofEndogenousIntelligence,CapabilityExposure,andDigitalTwin,thecollaborativeevolutionofsmallmodels,largemodels,andintelligentagentsenablesaneffec-tivebreakthroughoftechnologicalbottlenecks,

facilitatingtherealizationfromthevisionof“interconnectionofeverything”to“intelligentinterconnectionofeverything”.Thiswilllayarobusttechnologicalfoundationforthedigitaleconomyandtheintelligentsociety.Thisevolutionwillnotonlyredefinetheparadigmofthecom-municationsindustry,butalsopropelthedigitaltransformationacrossvariousindustriesintoanewstage,ultimatelymaterializingthevisionofanintelligentecosystemcharacterizedby“NetworksasaPlatform,CapabilitiesasaService”.

6GNETWORKSINTEGRATEDWITHAI

Copyright©CICTMOBILECO.,LTD.AllRightsReserved.NopartofthiswhitepapermaybereproducedortransmittedinanyformorbyanymeanswithoutpriorwrittenconsentofCICTMobileCo.,LTD.

Contents

Introduction 01

1/TransformationandTrendsinAI-6GIntegration 03

1.1CoreTransformationsinAI-6GIntegration 04

1.2TrendsinAI-6GIntegration 05

2/The6GIntelligentNetworkArchitecture 08

2.1Designprinciplesfor6Gintelligentnetwork 09

2.26Gintelligentnetworkarchitecture 11

3/6GNetworkEvolutionDrivenbyEndogenousIntelligence 15

3.16GEndogenousIntelligenceOperatingMechanism 16

3.2KeyTechnologiesfor6GEndogenousIntelligence 17

3.3DevelopmentTrendsof6GEndogenousIntelligence 23

4/EnablingEmergingApplicationsvia6GIntelligentCapabilityExposure24

4.1OperationMechanismofEnablingEmergingApplicationsvia6GIntelligentCapabilityExposure25

4.2KeyTechnologiesforEnablingEmergingApplicationsvia6GIntelligentCapabilityExposure26

4.3DevelopingTrendsofEnablingEmergingApplicationsvia6GIntelligentCapabilityExposure29

5/6GiNDTLeadstheNewParadigm 31

5.16GiNDTOperationalMechanism 32

5.2KeyTechnologiesofthe6GiNDT 34

5.3DevelopmentTrendsofthe6GiNDT 36

SummaryandProspect 38

Amidthefullcommercialdeploymentof5Gnetworksandtherapidadvancementofartificialintelligence(AI)technologies,thecommunicationsindustryisundergoingastrategictransformationfromtheInterconnectionofEverything(IoE)totheIntelligentInterconnectionofEverything(IIoE).Againstthisbackground,theevolutiontowardthesixth-generationmobilecommunicationsys-tem(6G)representsnotmerelyatechnologicalupgrade,butafundamentalparadigmshiftforthecommunicationsindustry.

Atpresent,thecommunicationsindustryisconfrontedwithunprecedentedchallengesandopportunities.EmergingservicessuchasExtend-edReality(XR)/holographiccommunication,distributedswarmintelligenceandnext-generationintelligentterminalshavenotonlyraiseddemandsforultra-highperformanceandextremeconnec-tivityofnetworks,butalsocreateddevelopmentopportunitiesfornewintelligentservices.Existing

communicationnetworkarchitecturesareunable

tomeettheprocessingrequirementsofthesenovelapplications,necessitatinganurgentupgradetowardintelligence.AItechnologiesneedtoevolvefromplayingtoolsinthe5Geratobecomingendoge-nouselementsof6G,deeplyintegratedintonetworkarchitectures,andenablethecorecapabilitiesincludingself-perception,self-decision-making,self-optimization,self-executionandself-evolution.Inthiscontext,6GnetworkswithdeepAIintegra-tionhaveemergedasaninevitabletrendforthe

developmentofthecommunicationsindustry. Rootedinthiserabackground,thisWhitePapersystematicallyelaboratesonthetransformativetrendsandtechnologicalpathwaysof6GnetworksdeeplyintegratedwithAI.Weproposethatthe

evolutionof6Gnetworksisanchoredinthree

corecharacteristics:endogenousintelligence,capabilityexposure,anddigitaltwin,withthegoalofbuildinganewgenerationofintelligent

informationandcommunicationinfrastructure.

EndogenousintelligencesignifiesthatAIwillbecomeanintrinsicendogenouselementofnet-workarchitectures,fullyenablingself-perception,self-decision-making,self-optimization,self-executionandself-evolution.CapabilityexposurereferstoprovidingAIcomputingpower,dataandservicecapabilitiesthroughanarchitecturewithexposureservices,therebyconstructingaservice-orientedsystemcharacterizedbyNetworksasanAIPlatform.DigitalTwinentailsleveragingdigitaltwinplatformstoaccelerateAImodeliterationandoptimizationthroughthedual-loopcollaborativemechanism—comprisinginternalclosed-loopverificationandexternalclosed-loopfeedback—whichisacoremechanismdefinedinthispaper.

Atthetechnicalarchitecturelevel,thisWhitePa-

perproposesahierarchicalintelligentarchitectureofcloud-network-edge-end,whereAIcapabilitiesareendogenouslyembeddedwithineverylayer.Theendlayerfocusesonlightweightinference,whilebasestationsandedgenodesdeliverreal-

6GNetworksIntegratedwithAI

Introduction

01

6GNetworksIntegratedwithAI

timeintelligentcomputing,thenetworklayerenablesregionalcollaborativeintelligence,and

thecentralintelligentbrainachievesglobaloptimalscheduling.Meanwhile,byadheringtodesignprinciples—includingtheservitizationof

AIelements,collaborativecontrolofAIresources

inmulti-dimensionalheterogeneousnetworks,

andcross-layer/end-to-endjointintelligentcol-laboration,weconstructanefficient,flexibleand

sustainableintelligentnetworksystemcapableofadaptingtotheevolutionofintelligentservices.

Attheapplicationlevel,thisWhitePaperfocusesonhowtheexposureof6Gintelligentcapabilitiesempowersnewapplications.6Gnetworkswillbenolongerlimitedtoprovidingbasicconnectivityservices,instead,asafoundationalintelligentinfrastructure,theyproactivelyexposurecorecapabilitiessuchasedgecomputingresources,networkdataandAImodels,andprovideend-to-endfull-linksupportforthedevelopmentanddeploymentofnewapplications.Throughthreekeyenablingtechnologies—namely,AImodellifecyclemanagement(LCM),cloud-network-edge-endAIcollaborativeempowerment,andAIserviceQualityofService(QoS)guarantee—weestablishacompleteempowermentchain.Thischaininte-gratescapabilityexposure,technologicalcollab-orativesupport,andAIvaluerealization,there-bybridgingthegapbetweennetworktechnicalcapabilitiesandindustrialapplicationdemands.Furthermore,thisWhitePaperpresentsan

in-depthanalysisofthenewparadigmfor6Gnetworksbroughtaboutbyintelligentdigitaltwin—acoreconceptof6Gendogenousintelligence.Drivenbythe6Gendogenousintelligentarchitec-ture,digitaltwinandAItechnologiesaredeeplyintegratedtoevolveintoanintelligentdigitaltwinsystemwithautonomousdecision-makingcapabilities.Throughacompleteclosedloopofdataperception,knowledgegenerationandstrategyimplementation,thesystemfacilitatesreal-time,dynamicandefficientcollaborationbetweenphysicalnetworksanddigitaltwins,andsupportsthefullLCMofnetworkoperationsandservice

innovation.

ThisWhitePaperiscompiledwiththeobjectivesofprovidingtheoreticalguidanceandpracticalreferencesforthedeepintegrationof6GnetworksandAItechnologies.ItseekstodrivetheleapfrogdevelopmentofthecommunicationsindustryfromIoEtoIIoE,andtolayasolidtechnologicalfoundationfortheconstructionofthedigitaleconomyandtheintelligentsociety.Bysystematicallyestablishingatechnologicalsystemcharacterizedbyendogenousintelligence,capabilityexposure,anddigitaltwin,6GnetworkswithdeepAIintegrationwillachieveaqualitativetransformationfrombeingatraditional“communicationpipeline”intoamodernintelligentservicehub.Thistransformationwillprovideapowerfulnewimpetusforthedigitaltransformationandintelligentupgradeofvarious

industriesworldwide.

02

01

TransformationandTrendsinAI-6GIntegration

The6Gnetwork,deeplyintegratedwithAI,addressescoredemandsarisingfromnovelterminalsandemergingapplications,suchasmulti-dimensionaldatafusionandintelligentarchitecture,anddrivescomprehensiveandprofoundtransformationsacrossthecommunicationsfield.

6G

6GNetworksIntegratedwithAI

04

1.1CoreTransformationsinAI-6GIntegration

The6Gnetworkhasevolvedbeyondamereinfor-

emergingserviceslikeXR/holographiccommuni-

mationtransmissionpipelineintoanewformof

cation.

digitalinfrastructurethatintegratesAI-powered

EndogenousIntelligenceofArchitecture:Bylever-

communication,sensing,andcomputingcapabil-

agingtechnologiessuchasintelligentairinterface,

ities.Thepursuitofultimateuserexperiencesby

distributedintelligentagents,andAI-nativeprotocol

emergingapplicationsandbusinessmodels,along

stacks,thisapproachovercomesthelimitationsof

withthedeepeningandexpansionofhigh-value

conventionalarchitecturesandenablesfull-domain

scenariosisdrivingthe6Gnetworktowardeven

coverageandubiquitousintelligentconnectivity.

higherlevel.

Multi-dimensionalDataFusion:Throughthe

BusinessModelInnovation:AIfacilitatesthe

integrationofcommunication,sensing,computing,

evolutionofmobilecommunicationservicestoward

andintelligence,aswellasthefusionanalysis

scenario-basedandcustomizedbusinessmodels.

ofmultimodaldata,anintent-drivenintelligent

Byleveragingtechnologiessuchasuserbehavior

networkoperationsystemisbuilttosupport

modelingandintelligenttrafficscheduling,6Gcan

scenariorequirementsinsmartcities,industrial

preciselyfulfillthedifferentiatedrequirementsof

Internet,andotherfields.

Drivenbytheaforementionedrequirements,theintegrationofAIand6Gnetworkswillbringaboutfour

majortransformations:

IntelligentUpgradingofApplicationScenarios:DrivingtheevolutionfromtheIoEtowardIIoE,andunleashingthefull-domainempowermentpotentialthroughdistributedintelligenceandnetworkcapabilityexposure.

RevolutionaryEvolutionofTerminalForms:Terminalsbreakthroughphysicallimitationsandevolveintointelligentagentterminals,becomingsmartnetworknodesequippedwithenvironmentalperceptionandcollaborationcapabilities.

IntelligentReconstructionofNetworkArchitecture:ThistransformationshiftstheroleofAIfromanexternal,AI-assistedparadigmtoanembeddedandAI-nativeintegrationwithinthenetworkarchitecture.Ittherebyendowsthenetworkwithpredictive,cognitive,andself-evolvingcapabilities.

IntegratedDevelopmentofServiceSystem:Ittransformsfrom“communication-centric”toatightly-coupledparadigmof“communication,sensing,intelligence,andcomputing”.Thisexpandsserviceboundariesfromsingularconnectivitytocomprehensiveintelligentenablement.

6GNetworksIntegratedwithAI

05

1.2TrendsinAI-6GIntegration

AIisemergingasacentraldriver,fundamentallyshapingtheevolutionof6Gnetworkarchitecture.Torealizethe6Gvisionof“ubiquitousintelligentconnectivity”,thenetworkarchitecturemustbedesignedaroundasystematictechnologicalframeworkcharacterizedbythreepivotalattrib-utes,includingendogenousintelligence,capabilityexposure,anddigitaltwin.Thissectionexamines

theadvantagesandlimitationsofkeyenablingtechnologies,proposesahierarchicalconvergencedevelopmentpathway,outlinestheevolutionarytimelinesanddeploymentrationalesfordistincttechnologicalcomponents,andoffersstrategicguidanceforthepracticalimplementationofintegratedsystems.

TrendsandCoreTechnologicalCharacteristics

Theexplosivegrowthoffutureapplicationsand

servicespresentsmultidimensionaltechnical

challengesinareassuchasairinterfaceefficiency,

networkarchitecture,andservicecapability.

Traditionalrule-drivenparadigmsstruggleto

addresstheserequirements,makingAItechnol-

ogyacriticalpathwayforovercomingexisting

bottlenecks.AnAI-integrated6Gnetworkmustbe

builtaroundfollowingthreecorecharacteristics:

First,an“endogenousintelligence”modeaims

toachieveself-perception,self-decision-mak-

ing,self-optimization,self-execution,andself-

evolution.Enabledbyadata-drivenclosed-loop

mechanismandahierarchicalcollaborativear-

chitecture,thisapproachachievesautonomous

operationanddeliversqualitativeimprovementsin

responsiveness,resourceutilization,autonomouscapabilityandadaptability.

Second,a“capabilityexposure”paradigmleverag-esanopenarchitecturetounleashmultidimensionaldataresources,AImodels,computingresources,andservicecapabilities.ThislowersthebarriertointegratingAIcomponentsandenhancestheefficiencyandeconomicvalueofresourceutilization.

Third,a“digitaltwin”capabilityreliesonadig-italtwinplatformtogeneratemassivevolumesofsimulationdata.Throughadual-loopcollaborativemechanismof“internalclosed-loopvalidationandexternalclosed-loopfeedback”,itacceleratestheiterativeoptimizationofAImodelsandprovidesavirtual-physicalintegratedenvironmentfortechnologyverificationandexploration.

CoreTechnologyAnalysis

Centeredonthevisionof“EndogenousIntelli-gence,CapabilityExposure,andDigitalTwin”,technologiessuchassmallAImodels,largeAImodels,intelligentagents,anddigitaltwinsserveaskeyenablers.Eachexhibitsdistinctadvantages,

applicationscenarios,andlimitations,whilealsofacingsharedoverarchingchallenges.

SmallAImodelsdemonstratestrengthsinhighefficiency,lowcomplexity,andhighaccuracy,andhavebeendeployedinfieldssuchasnetwork

6GNetworksIntegratedwithAI

06

optimizationandresourcescheduling.However,

theyareconstrainedbylimitedgeneralization

capabilityandreusability,requiringenhancements

inefficientmanagementandbroaderadaptability.

LargeAImodelsandintelligentagentspossess

corecapabilities,includingknowledgeextraction,

multimodaldatafusion,andcross-domaingen-

eralization,whichcandrivenetworkevolution

toward“intelligentandsimplifiedarchitectures”.

Keychallengesincludeensuringmulti-element

coordinationstability,balancingcomputational

demandswithperformance,andaddressingtrade-ofsbetweencompatibilityandsecurity.

DigitalTwinsenablefunctionalitiessuchasnetworkelementvirtualizationandenvironmentsimulation,alleviatingdatascarcityandshorteningalgorithmiterationcyclestosupportprecisenetworkoptimization.ThroughtightcouplingwithlargeAImodelsandintelligentagents,digitaltwinscanfacilitatetheprogressiverealizationofadvancedintelligentnetworkcapabilities.

HierarchicalConvergenceDevelopmentPathway

AI-integrated6Gnetworkswillevolveinalayeredandprogressivemanner.Atthenetworkelementlevel,thefocusisonhigh-performanceandhigh-efficiencydeployment.Thehigherlayeremphasizesmulti-taskandmulti-network-elementcollaborativeoptimization,whilethetoplayertargetsadvancedintelligenceenabledbylarge

AImodels.Smallmodelswillcontinuetoservespecificnicheusecases,whilelargemodelsandintelligentagentswillbeprogressivelyappliedforsystem-leveloptimization,ultimatelyformingalandscapeof“collaborationbetweensmallandlargemodels,withintelligenceempoweringalldomains”.

Thespecificevolutionpathwayencompassesthreekeydirections:

IntegrationofLargeAIModelswiththeNetwork

Thisprogressionwilloccurinstages,followingthesequencefrom“corenetwork”to“radioaccessnetwork”andfrom“operationalintelligenceto“runtimeintelligence”.Deploymentwilladopttwocomplementarymodes:“networkelementintegration”forreal-time,performance-criticalscenariosand“cloud-baseddeployment”orcompute-intensive,latency-tolerantscenarios.

Thisintegrationwillfirstmatureinoperationandmaintenancescenarios,subsequentlyexpandingtotheservicearchitecturelevel.Inthefuture,multi-agentsystemswillbedeployedtohandlecomplexcollaborativetasks,withstableoperationofsingleagentsasaprerequisite.

Integrationof

theNetworkand

IntelligentAgents

6GNetworksIntegratedwithAI

07

IntegrationofDigitalTwins

Thiscapabilitywillevolveprogressivelyfromthenetworkelementleveltothenetworklevelandultimatelythefull-domainlevel,enablingautonomousdecisionmakingandcoordinatedinteractionbetweenvirtualandphysicaltwinentities.

ResourceExposure

ModelExposure

ServiceExposure

Copilot

NetworkElementAgent

NetworkAgent

IntelligenceDigitalTwin

Model

Evaluation

NetworkOperationLargeModel

ChannelFoundationModel

FoundationModels

AirInterfacePerformance

RadioSystemPerformance

End-to-EndEfficiency

...

SmallModels

ApplicationLayer

ModelLayer

UseCase

ApplicationsforBusinessValue-OrientedApplicationScenarios

DigitalTwin

DataGeneration

Data

Preprocessing

Data

Maintenance

VectorDatabase

DataStorage

NetworkElementOperatingData

Application

Data

SubscriberProfile

Geographic

Information...

Communication

IndustryKnowledge

Data

Management

VerticallayerandData

Figure1-1AI-networkintegrationdevelopmentpath

TheAI-integrated6Gnetworkmustensurehighcoordinationamongnetworkfunctions,datamanagement,andcomputingresourcemanage-ment,whileexhibitingsufficientelasticityandscalability.ThearchitecturaldesignshouldembodycoreprinciplessuchasAIelementservitization,layereddistributedcollaborationandexposureofAIcapabilities,therebyestablishinganefficient,flexibleandsustainableintelligentnetworksystemthroughcomprehensivelifecyclemanagement.

Insummary,theAI-integrated6Gnetwork

representsaninevitabletrendintheevolutionofthecommunicationsindustry,drivingcomprehen-sivetransformationacrossnetworkarchitecture,servicesystems,applicationscenarios,andterminalforms.Anchoredinthecorecharacteristicsof“endogenousintelligence,capabilityexposure,anddigitaltwin”,andthroughthecoordinatedevolutionofsmallmodels,largemodels,intelligentagents,anddigitaltwins,itcaneffectivelyover-comeperformancebottlenecksandrealizethe6GvisionofadvancingfromtheIoEtoIIoE.

02

The6GIntelligentNetworkArchitecture

TheAI-integrated6Gnetworkisdrivingacomprehensivetransformationfromacommunicationinfrastructuretoaplatformforall-domainintelligence.Tomeetthediverseandscenario-specificapplicationdemandsofthefuture,the6GnetworkwilldynamicallyscheduleandintegratevariousAItechnologies.Itsfocusextendsbeyondoptimizingnetworkperformancetothecoreobjectiveofempoweringindustriesacrosstheboard,therebyprovidingefficientandpreciseintelligentservicestoallusers.Thisobjectiverequiresthat,fromthetop-leveldesignphase,the6GnetworkarchitectureachievestightcouplingbetweenconnectivitycapabilitiesandthethreecoreAIelements:computingresource,algorithmsanddata.Thisintegrationestablishesanativelyintelligent,all-domain6Gintelligentnetworksystem.

6G

Throughdistributeddeploymentandelasticcoordination,the6GnetworkcanprovideAIasaService(AIaaS)tonetworkoperatorsandexternalusersondemandandefficiently.Thisapproachnotonlyensuresthequalityandreliabilityofintelligentservicesbutisalsopivotalforenablingthenetworktoachievehigh-levelautonomyandprogresstowardself-optimization.Furthermore,thisexposedservicemodelwillpromotedeepintegrationandinnovationacrosstheintelligentecosystem.Intheco-evolutionofAItechnologiesandthe6Gnetwork,thenetworkarchitecturemustalsodemonstratestrongcompatibilityandscalabilitytoadapttorapidlyevolvingAIparadigmssuchaslarge-scalemodelsandintelligentagents.Thiswillcontinuouslyenhancetheservicecapabilityandadaptiveevolutionofthe6Gintelligentnetwork,solidifyingthefoundationforitstechnologicalimplementationandindustrialempowerment.

6GNetworksIntegratedwithAI

09

2.1Designprinciplesfor6Gintelligentnetwork

AI-as-a-Service:The6Gintelligentnetworkarchitectureshalldecouplecorecapabilitiessuchasconnectivity,computingresources,algorithms,anddataintomodularserviceunitsthatcanbeindependentlyinvoked.EachAIelementshallsupportelasticscalingbasedonactualdemand,e.g.computingresourcescanbedynamicallyscheduledaccordingtotrafficfluctuations,andalgorithmmodulescanbeiterativelyupdatedtosuitdiferentscenarios.Throughflexibleorchestration,variousAIelementscanbecombinedon-demandacrossdifferentnetworklayers.Thisbreaksdownresourcesilos,enhancesthereuseefficiencyandresponsespeedofintelligentservices,andenablesefficientcross-domainresourcesharing.

Multi-dimensionalHeterogeneousAIResourceCoordination:The6Gnetworkmustachieveintelligentcoordinationofmulti-dimensionalheterogeneousresources,includingspectrum,computingresources,anddata.ByleveragingAItodynamicallygenerateresourceallocation

strategies,thenetworkwillestablishacompleteclosed-loopmanagementcyclecomprisingdemandidentification,strategyformulation,andexecutionfeedback.Thisapproachmovesbeyondtradition-alstaticresourceallocation.Itenablespreciseresource-to-servicematchingandsignificantlyimprovesspectrumutilizationandcomputingenergyefficiency.

Cross-layer/End-to-EndJointIntelligentCoordination:6Gshallbreakdownthetraditionalboundariesamongthephysical,link,andap-plicationlayers,establishinganAI-based,end-to-endglobaloptimizationframework.Thisframeworkwillenablethedeepintegrationofunderlyingtransmissioncharacteristicswithupper-layerservicerequirements.Itwilleliminateinformationsilosinherentinlayeredarchitecturesandshiftoverallnetworkperformancefromlocaloptimizationtoaglobaloptimum.therebysubstantiallyenhancingend-to-endservicequality.

6GNetworksIntegratedwithAI

10

LayeredDistributedIntelligentCoordination:

The6Gnetworkwilladoptalayered“cloud-net-work-edge-end”architecture,withdifferentiatedAIcapabilitiesdeployedateachlevel,includingterminalsfocusingonlightweightinference,basestationsandedgenodesprovidingmorereal-timeintelligentcomputingthancloudservices,thenetworklayerenablingregionalcoordination,andacentralintelligententityachievingglobaloptimization.ThissupportsdistributedAImodeltrainingandinference,aswellasmulti-agentcollaborativedecision-making.Itpromoteshierarchicalintelligentcoordinationacrosstheentirechain.

EfficientDataFlowandAILifeCycleMan-agement(LCM)：Efficientdataflowiscentraltothe6Gintelligentarchitecture.Thearchitecturemustincorporaterobustcapabilitiesfordatacollection,preprocessing,storage,andtransmis-sion.Simultaneously,itmustembednativeAILCMtoenableclosed-loopcontrolovertheentireAIprocess,includingdatahandli