T∕NIDA 003-2025 规范规程标准Next Generation Network for 5.5G Era (NET5.5G) Deployment Guideline

NIDA-PD-003-2025

NIDA/TC/WG01/TF03Date:2025-09-26

NextGenerationNetworkfor5.5GEra(NET5.5G)DeploymentGuideline

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Contents

1Scope 1

2Normativereferences 1

3Termsanddefinitions 1

4Abbreviations 2

5Overviewofnextgenerationnetworkfor5.5GEra(Net5.5G) 3

6Architectureofnextgenerationnetworkfor5.5GEra(Net5.5G) 5

6.1ArchitectureofNet5.5G 5

6.2FeaturesandcapabilitiesofNet5.5G 6

7Advancedtechnologiesofnextgenerationnetworkfor5.5Gera(Net5.5G) 7

7.1Largedatatransmission-drivenphysicaldeviceimprovement 7

7.2Highefficienttransmission-drivennetworkenhancement 7

7.3Emergingserviceconnection-drivennetworknewgateways 8

7.4Largescalenetwork-drivenenhancednetworkmanagementandcontrol 9

7.5AI-drivennetworkintegratedintelligence 10

7.6high-securitytechnologies 11

8NextGenerationNetwork(Net5.5G)DeploymentSpecification 12

8.1Computingconnections 12

8.1.1Intra-DCintelligencecomputing 12

8.1.2Inter-DCintelligencecomputing 14

8.1.3Data-to-DC 16

8.2Intelligenceconnections 18

8.3Dataconnections 20

Bibliography 22

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Foreword

TheNetworkInnovationandDevelopmentAlliance(NIDA)isavoluntaryinternational,industry-specific,non-profitsocialorganizationcomprisedofindustryorganizations,universities,researchinstitutes,companies,andotherentitiesfromaroundtheworld,dedicatedtopromotingfixednetworktechnologyinnovationandindustrialupgrading.

TheworkofpreparingNIDAStandardsisnormallycarriedoutthroughtheNIDATechnicalCommittee(TC),its

WorkingGroups(WGs),andTaskForces(TFs).TheproceduresusedtodevelopthisdocumentandthoseintendedforitsfurthermaintenancearedescribedintheNIDAStandardsDevelopmentGuidelines.

Thisdocumentisdraftedby:ChinaUnicom,ChinaAcademyofInformationandCommunicationsTechnology,ChinaTelecommunicationsCorporation,InternetAssociationofKazakhstan,HuaweiTechnologiesCo.,Ltd.

Maindraftersofthisdocument:ChangCao,RanPang,ShuaiZhang,WeiGao,YongqingZhu,ZehuaHu,ShavkatSabirov,LiZhang,ShuanglongChen.

CopyrightNotice:

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ThisdocumentwaspreparedbytheTechnicalCommittee(TC),WorkingGroupWG01,NetworkEvolutionworkinggroup,TaskForceTF03,NextGenerationNetworkfor5.5GEra(NET5.5G)DeploymentGuideline.

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AnyfeedbackorquestionsonthisdocumentshouldbedirectedtotheNIDATCSecretariat.

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NextGenerationNetworkfor5.5GEra(NET5.5G)DeploymentGuideline

1Scope

ThisRecommendationdescribesgeneralprinciplesofnextgenerationnetworkfor5.5Gera(Net5.5G)deployment,thenspecifiesthearchitectureandkeytechnologiesforoverallnewthreeconnectionscenarios,includingcomputingconnections,intelligenceconnections,anddataconnections.

ThisRecommendationprovideskeytechnologiesforsupportofvariousapplicationsinNet5.5G.Followingthenetworkdeploymentguidelinewitharchitectureandkeytechnologiesforthethreescenariosareprovided.

2Normativereferences

[1].ITU-TY.LDTIMT-2020NetworksandBeyond:RequirementsandFrameworkforapplicationsdemandinglargedatatransmissions—Part6:Overviewofapplicationsdemandinglargedatatransmission

[2].WBBAWhitepaper(2024),NetworkEvolutionForthe5.5GAnd6GEra—NET5.5GNETWORKARCHITECTUREAND

KEYTECHNICALFEATURES

3Termsanddefinitions

3.1

Net5.5G

Net5.5Greferstothenextgenerationnetworkeratosupportcomputingconnection,intelligenceconnection,dataconnectionandspaceconnection.Itisdividedintotwophases,thisRecommendationfocusonphaseⅠ,includingthescenariosandkeytechnologiesofcomputingconnection,intelligenceconnectionanddataconnection.

3.2

Computingconnection

ComputingconnectionreferstothescenariossupportAItrainingandinference,e.g.,networkinasingledatanetwork(intra-DC),networkacrossmultipledatacenters(inter-DC)andnetworkfordatatransmissiontodatacenters(data-transmission-to-DC).

3.3

Intelligenceconnection

Intelligenceconnectionreferstothescenariossupportintelligentterminalsaccessandreference,e.g.,personalservices(e.g.,autonomousdrivingandXR),homeservices(e.g.,intelligentroboticvacuumcleanerandintelligentcamera)andindustryservices(e.g.,industryrobotsandintelligentmanufacturing).

3.4

Dataconnection

Dataconnectionreferstothescenariossupportdatatransferbetweendatasuppliersandconsumersfordifferentdatatypes(e.g.,privateandpublic)anddifferentscopes(e.g.,across-domainsandacross-countries.).

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4Abbreviations

ADN:AutonomousDrivingNetwork

AI:ArtificialIntelligent

AOI:AutomaticOpticalInspection

APN:Application-awareNetwork

APT:AdvancedPersistentThreat

DC:DataCenter

DT:DigitalTwin

ECMP:Equal-CostMulti-Path

ECN:ExplicitCongestionNotification

EDR:EndpointDetectionandResponse

HBF:HybridBeamforming

LLM:LargeLanguageModel

MAC:MediaAccessControl

MACsec:MediaAccessControlSecurityM&CManagementandControl

NSLB:NetworkScaleLoadbalancing

PFC:Priority-basedFlowControl

PQC:Post-QuantumCryptography

RDMA:RemoteDirectMemoryAccess

rPFC:RemotePFC

SLA:ServiceLevelAgreement

SASE:SpecialApplicationServiceElement

SPFC:SubscriberPFC

SRv6:SegmentRoutingIPv6

XR:ExtendedReality

WAN:WideAreaNetwork

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5Overviewofnextgenerationnetworkfor5.5GEra(Net5.5G)

Nextgenerationnetworkfor5.5GEra，abbreviatedasNet5.5G,referstothenetworkevolutionfortheemergingnetworkconnectionscenarios,includingcomputingconnection,intelligenceconnection,dataconnectionandairspaceconnection.

Figure1—OverviewofNet5.5G

Someorganizationshavealreadydonesomeresearch.WorldBroadbandAssociation(WBBA)haspublishedawhitepaper[1]aboutNet5.5G,whichfocusonasustainableevolutionofdatacommunicationnetworkinfrastructure,providingenhancedcapabilitiesinordertomeetthedemandsofnewintelligentapplicationtrends.ITU-TalsoproposedaRecommendation[2]aboutrequirementsandfunctionsforapplicationsdemandinglargedatatransmissions,whichdefinestheenhancedandnewfunctionsinIMT-2020networksandbeyondtomeettherequirementsofapplicationsdrivenbythenewtechnologies(e.g.,AI,cloud,bigdata,5Gand5G-A).

—Computingconnectionscenario

Computingconnectionreferstotheconnectionbetweencomputingpowersuppliersandconsumers.Net5.5Gforcomputingconnectionisusedtointerlinkthecomputingpowerandcomputingchips.It’srequiredtosupportthreetypesofnetworks,includingintra-datacenter,inter-datacenter,anddata-transmission-to-datacenter

Asfarasintra-DCnetwork,theinterconnectionofcomputingchipsneedstoaccommodatetheultra-large-scaleclusterconnectionsrangingfromhundredstotens,orevenhundredsofthousandsofchipsinonesingledatacenter.Thenetworkisrequiredtosupportultra-large-scalenetworking,highthroughputwithnodatalossesandintelligentfaulttolerance.

Asfarasinter-DCnetwork,themultidatacentercooperationforAItrainingisneededduetocomputingpowerandelectriclimitsofsingledatacenter.Thenetworkofinterconnectionofmultidatacentersneeds

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tosupporthighspeed,highthroughputandlong-distancelosslessdatatransmissioninordertosupporthigh-efficientultra-large-scalemodeltraining.

Thenetworkofdata-to-DC,servingasapipelineforcomputingpower,connectsalargenumberofenterprises,researchinstitutionsanddatacenters.It’srequiredtohavethecapabilitiesfordifferentiatedschedulingandoptimization.AIlargemodeltrainingincurslargedatatransmissionrequirements.ThemodeldatasetusuallyrequiretenofGBtohundredsofTBdata.Thechallengesoflargedatatransmissiontodatacenterareincludeshighbandwidthlowcost,highnetworkresourceutilizationandhighdatasecurity.

—Intelligenceconnectionscenario

WiththedevelopmentsofGenerativeAI,multimodalunderstandingandembodiedintelligence,thereal-timeinteractionbetweenvirtualandtherealworldisdeepening.AIagentaredeeplyintegratedwithvariousintelligentterminalstocreatemoreinnovativeapplicationscenarios.AIterminals,representedbyAIassistants,embodiedrobotsandimmersivedevices,havehadasignificantimpactonlifeandproduction.Net5.5Gforintelligenceconnectionisrequiredtosupporttheindividual,home,enterpriseandindustryscenarios.

Forindividualscenario,AIterminalsanddigitalhumans,astheentriesforconnectingpeopleandAI,reshapingthenewman-machinerelationship,anddrivethenetworkarchitecturetransformationofmulti-levelinference.Thenetworkbetweenterminalsandcloudisrequiredtomeetthehighbandwidthandlowlatencyrequirements.

Forhomescenario,aninterconnectedhomeintelligentecosystemwithcompanionrobotsasthecorehasbecomethemainstream.Inadditionoflow-latencyexperience,thenetworkinhomescenarioisalsorequiredtoprovidesecurityauthenticationanddataencryptionfunctions.

Forenterprisescenario,newtechnologiessuchasimmersivecollaborativeoffice,AIassistantandintelligentmanufacturingrobotshavebeenappliedrapidly,withstrongerinteraction,higherproductionefficiency,andtheman-man,man-machine,andmachine-machinerelationshipcloselyimplemented.Thenetworkisrequiredtoensurethevirtualandrealityconvergenceexperience,lowlatency,centimeter-levelpositioning,application-levelpolicycontrol,anddimensionaldataprotection.

—Dataconnectionscenario

Datahasbecometheimportantfactorofproductionnow.Thedataelementneedstobecirculatedacrossdifferentindustries,regionsandsubjects.Net5.5Gfordataconnectionisanewgenerationofsecureandtrustworthynetworkinfrastructuretosupportdataelementcirculation.

Dataconnectionsnetworkisrequiredtosensordataidentities,typesandsensitivitylevelsandthenimplementthesecuritycontrolpolicies,inordertoimplementmanageableandcontrollabledataelementcirculationpaths.

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Dataconnectionnetworkshouldhavethecapabilitiesofdifferentiateddatatransmissiontrustedpathsandhighersecuritydatatransmissionencryption,inordertomeetthesecurityrequirementsofdataelementcirculationindifferentindustriesandatdifferentdatalevels.

Dataconnectionnetworkisrequiredtoprovidedataaccessnodes,andshouldhastheall-in-onecapabilitiesofnetwork,dataandsecurity.Basedonthezero-trustarchitecture,thenetworkshouldsupportthedatasecurityenhancementcapabilitiessuchassecuredatastorage,refineddatausecontrol,andsecuredatatransmission,toimplementflexibleandsecuredataaccessandloweringthethresholdforcustomer’sdataconnection.

6Architectureofnextgenerationnetworkfor5.5GEra(Net5.5G)

6.1ArchitectureofNet5.5G

Thenextgenerationnetworkfor5.5Gera(Net5.5G)isshowninthefollowingfigure:

Figure2—ArchitectureofNextGenerationNetworkfor5.5GEra(Net5.5G)

Thearchitectureofnextgenerationnetworkfor5.5GEra(Net5.5G)isdividedintofivelayers,physicaldevicelayer,physicalnetworklayer,serviceconnectionlayer,networkmanagementandcontrollayer,andoperation

layer.

Intermsofphysicaldevicelayer,avarietyofdevicesshouldbesupported,includingrouters,switches,terminaldevices,andsoon.

Intermsofphysicalnetworklayer,inordertoconnectthepersonalsmartterminals,homesandenterprisesandmulti-levelinferenceanddatacenters,whichareusedtosupportAIlargemodeltrainingandinference

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andnewAI-drivenapplications,Net5.5Gneedstobuildhigh-qualityedgenetworks,intra-DCnetwork,inter-DCnetworkanddata-to-DCnetwork.Atthesametime,spaceandterrestrialintegrationnetworksisalsoneeded.

Intermsofserviceconnectionlayer,theservicegateways(e.g.,intelligencegateway,datagateway,data-to-DCgatewayandinter-DCgateway)areneededtoconnecttheusers,computingpoweranddata.

Intermsofnetworkmanagementandcontrollayer,Net5.5Gshouldbecomposedofmulti-regioncontrollersasnetworkbraintoprovidevariousofnetworkmanagement,operationsandmaintenancecapabilitiestoimprovethenetworkautonomouslevel.

Intermsofoperationlayer,whichusuallyworksasacoordinatorbetweenbusinessservicesandnetwork,isalsorequiredtobeimproved.

Inaddition,asthefoundationalattribute,hierarchicalsecurityprotectionisrequiredindifferentlayers.

6.2FeaturesandcapabilitiesofNet5.5G

Tosupportnewconnectionscenarios,nextgenerationnetworkfor5.5GEra(Net5.5G)isrequiredtoachievenewnetworkobjectivesinthefollowingfigure:

Figure3—ObjectivesofNextGenerationNetworkfor5.5GEra(Net5.5G)

Toachievethegoalofhigh-qualityCampus,high-throughputconvergedbearerandhigh-computingefficiencydatacenter,thefollowingkeyfeaturesandcapabilitiesarerequired:

—Extremesimplificationandultra-bandwidth:Thenetworkshouldbeextremelysimplified.Thenetworkdevicesshouldsupporthigh-densityportsandultra-bandwidth,basedonthecontinuallybandwidthvolumeimprovementofthephysicallayerprotocols(e.g.,Wi-Fi7and400GE/800GE/1.6TE).

—Intelligencenative:Theserviceconnectionlayerisrequiredtosupportfineapplicationidentification,andthephysicalnetworklayerisrequiredtosupportlosslesshighthroughput.Bothphysicaldevicelayer

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andnetworkmanagementandcontrollayershouldevolvetowardsintelligentinordertosupportautonomousdrivingnetwork(ADN)tolevel4orevenmoreadvanced.

—Integratedsecurity:Thedevicesshouldhavenativesecurity,andthephysicalnetworklayershouldsupportsecuretransporttunnels.Inserviceconnectionlayer,theserviceconnectionsecurityshouldbeguaranteedthroughdifferentmethodssuchasdataandnetworkcooperation,dataanti-ransomwareandsoon.Thenetworkmanagementandcontrollayersupportintegrated

—Greenandenergysaving:Thephysicaldevicesshouldsupporthibernationondemand,andthephysicalnetworklayerisrequiredtosupportlow-carbonpaths.Thenetworkmanagementandcontrollayershouldsupportvisibilityandcontrollability.

7Advancedtechnologiesofnextgenerationnetworkfor5.5Gera(Net5.5G)

7.1Largedatatransmission-drivenphysicaldeviceimprovement

Keytechnologiesinphysicaldevicelayerreferstothecapabilitiestoenhancebandwidth,reducepowerconsumption,increaseportandbandwidthvolumetomeettherequirementoflargedatatransmission.Thefollowingtechnologiesshouldbeconsidered:

—Highdatarateof400GE/800GE/1.6TE:Innetworksystem,highdatarateEthernetportswithlowpowerperbitdesignandadvancedsignalprocessingtechnologiesshouldbeusedtosupporthigh-speed,low-latencyandhigh-reliabilitydatatransmission.

—EvolutionofWi-Fi7[3]:Millimeterwavetechnologypromotestheaccessbandwidthoverairinterfacefrom30Gbpsto100Gbps.Technologiessuchashigh-gainalgorithmanddielectricHBFantennasareusedtocontinuouslychallengethecoveragedistanceof10mto15munderpowerconsumptionconstraints.Thisisurgentlyneededinlargeuplinkscenarios,suchasindustrialAOIbackhaulandXRvideolocalgeneration.

—Switcheswithhigh-densityports:Theseswitches,suchassubrack-shapedswitchesshouldbeusedinlargescalenetworks(e.g.,tensof,evenhundredsofthousandsofchips)tosupportAIlargemodeltrainingandinference.

7.2Highefficienttransmission-drivennetworkenhancement

Keytechnologiesofprotocolsareusedtoimplementlarge-scalenetwork,simplifynetworkinterconnections,supportlosslesshighthroughputandenhancenetworksecurity.Thefollowingtechnologiesshouldbeconsidered:

—Ethernetenhancement:ConvergedEthernetistheoptimalprotocolinAItrainingandinference.EnhancedEthernettechnologiesshouldbeconsidered,e.g.,headsuppression,linklayerretransmission.

—SegmentRoutingIPv6(SRv6)[4]:SRv6isthelastevolutionofthesource-routingtechnology.It’scompatiblewithIPv6,andcanbeusedtosimplifynetworkprotocols,specifyexplicitforwardingpaths,andtosupportcross-domainnetworkpathprogramming.Inaddition,SRv6isbasedon128bitsaddressspace,whichcouldbeusedtoidentifyvariousnetworkinformation,locations,VPNs,value-added

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applications,etc.TheprogrammabilityofSRv6isusefultoimplementflexiblenetworkfunctions.SomeenhancecapabilitiesofSRv6areasfollows:

lApplication-awarenetwork(APN)[5]isusedtoidentifyapplication.ThiscapabilitywillpromotethenetworkservicesystemfromIPaddressonlytoIPaddressandAPNID,toprovidemorerefine(e.g.,application-level)networkservice.Italsosupportsthecollaborationofclouds,networks,edgesandendpointstoguaranteetheapplicationexperience.

lAPNisusedtoidentifydataattributetypesanddataspacetoensurethatdataisrecognizable,manageable,andvisibleduringdatatransfer,ensuredatasecurity,andpromotedatadevelopmentandutilization.

—Accuratetrafficdatameasurement:Advancedtrafficdatameasurementmethodsarerequiredtodetecttherealflowstatusinsteadofthetraditionalprobepacket-basedmeasurementmethods.Theadvancedtrafficdatameasurementmethods,suchasin-situflowinformationtelemetry(IFIT)[6],encapsulatethemeasurementinformationinthetrafficdatapackets,whichcanprovidehighaccuratelyend-to-endandhop-by-hopmeasurementforaflowwithrespecttopacketloss,latencyandjitter.

—Networkslicing:IPv6-enhanced-basednetworkslicescanbeusedtoimplementresourceandsecurityisolation,differentiatedservicequalityassurance,flexibleandcustomizabletopologyconnection.

—Technologiesfornetworkloadbalance:Toaddressdisadvantagesofthetraditionalequal-costmulti-path(ECMP)innetworkloadbalance,enhancedtechnologies,suchaspacketspraying,shouldbeused.

—Preciseflowcontrol:Flowcontroltechnologies,e.g.,priority-basedflowcontrol(PFC)[7]withoutdeadlockandhead-of-lineblocking,shouldbeusedtopreventpacketlossindatanetwork.Tosupportintelligentcomputingacrosswideareanetwork(WAN)withlongdistancebetweendatanetworks,precisecontroltechnologiesarerequired.SubscriberPFC(SPFC)isatechnologydesignedtoenhancedsubscriber-levelflowcontrolbasedonSRv6network.ThecollaborationofSPFConWANandPFCorrPFCindatacentercouldenablethelosslesshighthroughputfortheAItraining.

—Congestioncontroltechnologies:Congestioncontrolreferstothecongestiondetection,avoidanceandprocessing.InAItrainingscenarios,congestioncontroltechnologiesforRDMAflowsshouldbeusedtoreducethenetworkcongestion.TechnologiessuchasECN,fastCNP,andAIenabledECNshouldbetakenintoconsidered.Besides,adaptiveroutingshouldbeintroducedtoimprovethecongestiondetection,distributionandre-routingefficiency.

—Bigflowrecognition:Thistechnologyisrequiredtorecognizethelargeflowsinthenetworkapproximatelyreal-time.

7.3Emergingserviceconnection-drivennetworknewgateways

Workastheservicegatewaysofintelligenceconnection,dataconnectionandtransmissiontoDC,newtechnologiesarerequiredtoconnecttheusers,computingpoweranddata:

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—Computingpowergateway:ThesegatewaysarerequiredtoconnecttheusersandDCs.

lGatewayfordata-to-DCarerequiredtobedeployedonbothenterprisesidesandcomputingpowercenters.Thesegatewaysprovideprotocoltransformattransportlayer,allocateidentificationandselectpropertunnelsandpathstodatatransmissiontoDCs,andsupportaccountingandreconciliationcapabilities.

lGatewaysforinter-DCconnectionsarerequiredtobedeployedincomputingpowercenters.Thesegatewayssupportprotocolconnectionstoprovideultra-highbandwidthandlong-distancelosslessforwardingpathsforcollaborativetrainingofmultipleDCs.

—Intelligencegateways:Thesegatewaysrefertovarioustypesofintegratedservicegatewaysthatestablishconnectionswithmulti-levelinferencecenterstodynamicallyselectproperinferencemodetoensuresmoothrunningofdifferentservices.

lAstheserviceentrances,gatewaysidentifyandcontrolapplications,andworkwithmulti-layerreferencetomeetthedifferentiatedrequirementsofvariousapplications.

lThegatewaysserveasthecontrolpointfordataencryptionandsecuritypoliciestoensuredatasecurity.

lThesegatewaysshouldbedeployedindifferentlevels,e.g.,campus,carrieredgenetworkanddatacenter.

lThesegatewayscanworkasanedgeinferencenode.

—Datagateways:Thesegatewaysprovidemulti-scenariocapabilitiesfordataproximityandtrustedaccess,APNnetworkcollaboration,anddatafencingforbothdatasuppliersandconsumers.

lThroughthenetworkanddatasecurityconvergenceaccessnode,theidentity,device,dataofthedatasuppliersandconsumerscanbetrustedtoaccesstheconnectingdatanetworks,andthedatacanbeencryptedstoredandusedcontrolpoliciescanbespecified.

lThedatagatewaysusenetworklabels,e.g.,APN6,tocarrydatainformation,useridentity,datatypes,sensitivitylevels,etc.,toensurethatthedataarestrictly,accuratelyusedastheusagecontrolpoliciesformulatedbydatasuppliers,andtoprotectdatasovereignty.

lThedatagateway,byrecognizingtheauthorizeddatausagescope(e.g.,countriesandindustries)carriedbynetworklabels,applypolicycontrolsuchasblockingandin-depthanalysisofdataflowbeyondtheauthorizedscope,toimplementdatafenceduringdatatransfer.

7.4Largescalenetwork-drivenenhancednetworkmanagementandcontrol

Workasthenetworksmartbrain,networkM&Clayerrequireadvancedkeytechnologiestopromotethenetworkautonomoustolevel4oradvanced.ThetechnologiesofM&Clayershouldcollaboratewiththetechnologiesofdevicetorealizenetworkself-perception,self-management,self-optimizationandself-healing.Thefollowingtechnologiesshouldbeconsidered:

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—Centralizedpathcomputing,re-optimizationandscheduling:Thistechnologycalculatestheoptimaltrafficdistributionbydrawingaglobaltrafficmatrixandautomaticallydivertstrafficthroughnetworkdevices.Basedonthemulti-dimensionaldataofthenetworks,applications,AItasks,implementintelligentalgorithms,largeflowrecognition,e.g.,network-scaleloadbalancing(NSLB),cloud-map,maximumfluxalgorithm.

lTheNSLBtechnologytakesadvantageoftheglobalperspectiveofbothnetworkandAItrainingtasks,achieving100%networkwidetrafficbalancingandimprovingperformanceinAItrainingscenarios.

lCloud-mapalgorithmtakeallthenetworkandcloudresourcesasthecomputefactorstocalculatethemostproperpathandrecommendpropercloud.

lMaximum-throughputmulti-pathalgorithmfocusoncomputingflexiblemultiplepathstocarrythelargedatatransmissiontothecloudsite.

lBasedonthebigflowrecognition,flow-levelschedulingisusedtomatchtheflowtotheoptimalpaths,inordertorealizehighnetworkthroughput.

—Application-levelexperienceguaranteeisrequiredtoidentifytheapplications,perceivetheapplicationstatusandimplementclose-looppoliciestoguaranteethea