Cloud RAN for Mobile Networks - a Technology Overview

Cloud RAN or Small Cells?Joe Madden, Mobile ExpertsApril 2013It’s funny to watch the industry hype machine at work. Every new idea that comes along is promoted as the “next big thing”. In the case of Cloud RAN, we have seen several vendors promoting their trials and initial deployments, and we have all heard about the savings available in baseband pooling. Cloud RAN will make dense urban networks possible, and putting the baseband processing together will make LTE-Advanced features possible.At the same time, small cells have also been advertised as the solution to the same high-density traffic problem. Instead of pooling baseband resources, small cells distribute the baseband processing. So which is it? Are we going to bring the baseband processing together, or spread it out?Both technologies are promoted as a way to save cost. The Cloud RAN architecture is intended to save operational cost, by locating everything together and allowing a technician to work more efficiently in maintaining baseband resources. Cloud RAN also enables LTE-Advanced features which improve capacity.It’s true that Cloud RAN makes LTE-Advanced easier to implement. Coordinated Multi-Point (CoMP) requires very low latency (less than 1-2 microseconds) to provide a big boost in capacity. Enhanced Inter-Cell Interference Coordination (eICIC) coordinates blank and almost-blank subframes on a real-time basis, so locating the baseband processing in one place greatly reduces the complexity of coordinating changes on the fly. The Serdes interface to a Remote Radio Head is the lowest-latency connection possible, with most of the delay coming from physical propagation instead of IPSec and processing time. As a result, multiple RRH units on a single baseband node offers the highest performance boost from CoMP..The financial benefit of CoMP comes from the added capacity and higher throughput available at the cell edges. CoMP can improve throughput by as much as 80% at the cell edge, for both uplink and downlink. Using a traditional macro network as a baseline, the overall savings can be very significant in dollar value because fewer macro eNodeBs are required. Additional savings come from the centralized location of the baseband processing, making maintenance simpler and more efficient.The Small Cell architecture is also intended to reduce cost per bit, by reducing the overall cost of baseband processing and radio hardware, as well as increasing spectral efficiency and overall throughput. Small Cells can drop the cost per bit by a factor of 4, compared to a macro LTE network. Even with high-cost backhaul such as millimeter-wave links, the cost per bit can drop in half.So which architecture gives a bigger impact to the guys in Accounting? It looks like the answer to that question is “it depends”. The Cloud RAN architecture is favored by operators with access to cheap fiber (China Mobile, NTT DoCoMo, SKT, KT), and in other cases only for stadium situations or other localized problems. The Small Cell architecture seems to be popular with most mobile operator CFOs, because the transport cost for RRH fiber outweighs the operational savings of co-locating the baseband processors. As examples, China Mobile and NTT DoCoMo like C-RAN because they own the fiber in their countries. Competitors such as China Unicom and Softbank like small cells because they pay much higher cost for fiber bandwidth.Will mobile operators discover more value in Cloud RAN when CoMP and eICIC are widely adopted? Maybe. But the Cloud RAN promoted so far doesn’t change the economics of a macro network by a factor of 4. For wider adoption, Cloud RAN must achieve some significant savings to overcome the penalty of high transport cost. At the same time, CoMP and eICIC will be implemented with small cells, and while the benefit may be smaller, we can expect significant benefits from these features in a HetNet configuration.In the end, most operators will be pushing ahead with the Small Cell architecture, and may consider Cloud RAN for special situations such as a stadium with very high density. If fiber bandwidth is free, then the cost of transport is no big deal, and Cloud RAN is attractive. For most operators around the world, fiber cost is a significant chunk of their operating budget, so we expect most of the market to move toward Small Cells.。

38.300-⽆线接⼊⽹（NG-RAN）概述和总体描述英⽂原版3GPP TS38.300V15.5.0(2019-03)Technical Specification3rd Generation Partnership Project;Technical Specification Group Radio Access Network;NR;NR and NG-RAN Overall Description;Stage2(Release15)The present document has been developed within the3rd Generation Partnership Project(3GPP TM)and may be further elaborated for the purposes of3GPP. The present document has not been subject to any approval process by the3GPP Organizational Partners and shall not be implemented.This Specification is provided for future development work within3GPP only.The Organizational Partners accept no liability for any use of this Specification. Specifications and Reports for implementation of the3GPP TM system should be obtained via the3GPP Organizational Partners'Publications Offices.3GPPPostal address3GPP support office address650Route des Lucioles-Sophia AntipolisValbonne-FRANCETel.:+33492944200Fax:+33493654716Internet/doc/2e6bf4e527c52cc58bd63186bceb19e8b8f6ecf2.htmlCopyright NotificationNo part may be reproduced except as authorized by written permission.The copyright and the foregoing restriction extend to reproduction in all media.2019,3GPP Organizational Partners(ARIB,ATIS,CCSA,ETSI,TSDSI,TTA,TTC).All rights reserved.UMTS?is a Trade Mark of ETSI registered for the benefit of its members3GPP?is a Trade Mark of ETSI registered for the benefit of its Members and of the3GPP Organizational Partners LTE?is a Trade Mark of ETSI registered for the benefit of its Members and of the3GPP Organizational Partners GSM?and the GSM logo are registered and owned by the GSM AssociationContentsForeword (7)1Scope (8)2References (8)3Abbreviations and Definitions (9)3.1Abbreviations (9)3.2Definitions (11)4Overall Architecture and Functional Split (11)4.1Overall Architecture (11)4.2Functional Split (12)4.3Network Interfaces (14)4.3.1.1NG User Plane (14)4.3.1.2NG Control Plane (14)4.3.2Xn Interface (15)4.3.2.1Xn User Plane (15)4.3.2.2Xn Control Plane (16)4.4Radio Protocol Architecture (16)4.4.1User Plane (16)4.4.2Control Plane (17)4.5Multi-Radio Dual Connectivity (17)5Physical Layer (17)5.1Waveform,numerology and frame structure (17)5.2Downlink (18)5.2.1Downlink transmission scheme (18)5.2.2Physical-layer processing for physical downlink shared channel (18) 5.2.3Physical downlink control channels (19)5.2.4Synchronization signal and PBCH block (20)5.2.5Physical layer procedures (20)5.2.5.1Link adaptation (20)5.2.5.2Power Control (21)5.2.5.3Cell search (21)5.2.5.4HARQ (21)5.2.5.5Reception of SIB1 (21)5.3Uplink (21)5.3.1Uplink transmission scheme (21)5.3.2Physical-layer processing for physical uplink shared channel (22) 5.3.3Physical uplink control channel (22)5.3.4Random access (23)5.3.5Physical layer procedures (23)5.3.5.1Link adaptation (23)5.3.5.2Uplink Power control (23)5.3.5.3Uplink timing control (23)5.3.5.4HARQ (24)5.4Carrier aggregation (24)5.4.1Carrier aggregation (24)5.4.2Supplementary Uplink (24)5.5Transport Channels (24)6Layer2 (25)6.1Overview (25)6.2MAC Sublayer (27)6.2.1Services and Functions (27)6.2.2Logical Channels (27)6.2.3Mapping to Transport Channels (27)6.3RLC Sublayer (28)6.3.1Transmission Modes (28)6.3.2Services and Functions (28)6.3.3ARQ (28)6.4PDCP Sublayer (29)6.4.1Services and Functions (29)6.5SDAP Sublayer (29)6.6L2Data Flow (29)6.7Carrier Aggregation (30)6.8Dual Connectivity (31)6.9Supplementary Uplink (31)6.10Bandwidth Adaptation (31)7RRC (32)7.1Services and Functions (32)7.3System Information Handling (33)7.3.1Overview (33)7.3.2Scheduling (35)7.3.3SI Modification (35)7.4Access Control (35)7.5UE Capability Retrieval framework (35)7.6Transport of NAS Messages (36)7.7Carrier Aggregation (36)7.8Bandwidth Adaptation (36)7.9UE Assistance Information (36)8NG Identities (36)8.1UE Identities (36)8.2Network Identities (37)9Mobility and State Transitions (37)9.1Overview (37)9.2Intra-NR (38)9.2.1Mobility in RRC_IDLE (38)9.2.1.1Cell Selection (38)9.2.1.2Cell Reselection (39)9.2.1.3State Transitions (39)9.2.2Mobility in RRC_INACTIVE (41)9.2.2.1Overview (41)9.2.2.2Cell Reselection (42)9.2.2.3RAN-Based Notification Area (42)9.2.2.4State Transitions (42)9.2.2.4.1UE triggered transition from RRC_INACTIVE to RRC_CONNECTED (42)9.2.2.4.2Network triggered transition from RRC_INACTIVE to RRC_CONNECTED (44) 9.2.2.5RNA update (45)9.2.3Mobility in RRC_CONNECTED (47)9.2.3.1Overview (47)9.2.3.2Handover (48)9.2.3.2.1C-Plane Handling (48)9.2.3.2.2U-Plane Handling (50)9.2.3.2.3Data Forwarding (52)9.2.3.3Re-establishment procedure (53)9.2.4Measurements (53)9.2.5Paging (56)9.2.6Random Access Procedure (56)9.2.7Radio Link Failure (57)9.2.8Beam failure detection and recovery (58)9.3Inter RAT (58)9.3.1Intra5GC (58)9.3.1.1Cell Reselection (58)9.3.1.2Handover (58)9.3.2From5GC to EPC (59)9.3.2.1Cell Reselection (59)9.3.2.2Handover and redirection (59)9.3.2.3Measurements (59)9.3.2.4Data Forwarding for the Control Plane (59)9.3.2.5Data Forwarding for the User Plane (60)9.3.3From EPC to5GC (60)9.3.3.1Data Forwarding for the Control Plane (60)9.3.3.2Data Forwarding for the User Plane (60)9.4Roaming and Access Restrictions (61)10Scheduling (61)10.1Basic Scheduler Operation (61)10.2Downlink Scheduling (61)10.3Uplink Scheduling (62)10.4Measurements to Support Scheduler Operation (62)10.5Rate Control (63)10.5.1Downlink (63)10.5.2Uplink (63)10.6Activation/Deactivation Mechanism (63)10.7E-UTRA-NR Cell Resource Coordination (64)11UE Power Saving (64)12QoS (65)12.1Overview (65)12.2Explicit Congestion Notification (67)13Security (67)13.1Overview and Principles (67)13.2Security Termination Points (69)13.3State Transitions and Mobility (70)14UE Capabilities (70)15Self-Configuration and Self-Optimisation (70)15.1Definitions (70)15.2Void (70)15.3Self-configuration (70)15.3.1Dynamic configuration of the NG-C interface (70)15.3.1.1Prerequisites (70)15.3.1.2SCTP initialization (71)15.3.1.3Application layer initialization (71)15.3.2Dynamic Configuration of the Xn interface (71)15.3.2.1Prerequisites (71)15.3.2.2SCTP initialization (71)15.3.2.3Application layer initialization (71)15.3.3Automatic Neighbour Cell Relation Function (72)15.3.3.1General (72)15.3.3.2Intra-system Automatic Neighbour Cell Relation Function (72) 15.3.3.3Void (73)15.3.3.4Void (73)15.3.3.5Inter-system Automatic Neighbour Cell Relation Function (73) 15.3.4Xn-C TNL address discovery (74)15.4Support for Energy Saving (75)15.4.1General (75)15.4.2Solution description (75)15.4.3O&M requirements (75)16Verticals Support (76)16.1URLLC (76)16.1.1Overview (76)16.1.2LCP Restrictions (76)16.2IMS Voice (77)16.2.0Support for IMS voice (77)16.2.1Support for MMTEL IMS voice and video enhancements (77) 16.2.1.1RAN-assisted codec adaptation (77)16.2.1.2MMTEL voice quality/coverage enhancements (78)16.3Network Slicing (78)16.3.1General Principles and Requirements (78)16.3.2AMF and NW Slice Selection (80)16.3.2.1CN-RAN interaction and internal RAN aspects (80)16.3.2.2Radio Interface Aspects (80)16.3.3Resource Isolation and Management (80)16.3.4Signalling Aspects (80)16.3.4.1General (80)16.3.4.2AMF and NW Slice Selection (80)16.3.4.3UE Context Handling (81)16.3.4.4PDU Session Setup Handling (81)16.3.4.5Mobility (82)16.4Public Warning System (83)16.5Emergency Services (83)16.5.1Overview (83)16.5.2IMS Emergency call (83)16.5.3eCall over IMS (84)16.5.4Fallback (84)Annex A(informative):QoS Handling in RAN (85)A.1PDU Session Establishment (85)A.2New QoS Flow with RQoS (85)A.3New QoS Flow with Explicit RRC Signalling (86)A.4New QoS Flow with Explicit NAS Signalling (87)A.5Release of QoS Flow with Explicit Signalling (88)A.6UE Initiated UL QoS Flow (88)Annex B(informative):Deployment Scenarios (90)B.1Supplementary Uplink (90)B.2Multiple SSBs in a carrier (90)Annex C(informative):I-RNTI Reference Profiles (92)Annex D(informative):SPID ranges and mapping of SPID values to cell reselection andinter-RAT/inter frequency handover priorities (93)Annex E(informative):Change history (94)ForewordThis Technical Specification has been produced by the3rd Generation Partnership Project(3GPP).The contents of the present document are subject to continuing work within the TSG and may change following formal TSG approval.Should the TSG modify the contents of the present document,it will be re-released by the TSG with an identifying change of release date and an increase in version number as follows:Version x.y.zwhere:x the first digit:1presented to TSG for information;2presented to TSG for approval;3or greater indicates TSG approved document under change control.y the second digit is incremented for all changes of substance,i.e.technical enhancements,corrections, updates,etc.z the third digit is incremented when editorial only changes have been incorporated in the document.1ScopeThe present document provides an overview and overall description of the NG-RAN and focuses on the radio interface protocol architecture of NR connected to5GC(E-UTRA connected to5GC is covered in the36series).Details of the radio interface protocols are specified in companion specifications of the38series.2ReferencesThe following documents contain provisions which,through reference in this text,constitute provisions of the present document.-References are either specific(identified by date of publication,edition number,version number,etc.)or non-specific.-For a specific reference,subsequent revisions do not apply.-For a non-specific reference,the latest version applies.In the case of a reference to a3GPP document(includinga GSM document),a non-specific reference implicitly refers to the latest version of that document in the sameRelease as the present document.[1]3GPP TR21.905:"Vocabulary for3GPP Specifications".[2]3GPP TS36.300:"Evolved Universal Terrestrial Radio Access(E-UTRA)and Evolved UniversalTerrestrial Radio Access Network(E-UTRAN);Overall description;Stage2".[3]3GPP TS23.501:"System Architecture for the5G System;Stage2".[4]3GPP TS38.401:"NG-RAN;Architecture description".[5]3GPP TS33.501:"Security Architecture and Procedures for5G System".[6]3GPP TS38.321:"NR;Medium Access Control(MAC)protocol specification".[7]3GPP TS38.322:"NR;Radio Link Control(RLC)protocol specification".[8]3GPP TS38.323:"NR;Packet Data Convergence Protocol(PDCP)specification".[9]3GPP TS37.324:"NR;Service Data Protocol(SDAP)specification".[10]3GPP TS38.304:"NR;User Equipment(UE)procedures in idle mode".[11]3GPP TS38.306:"NR;User Equipment(UE)radio access capabilities".[12]3GPP TS38.331:"NR;Radio Resource Control(RRC);Protocol specification".[13]3GPP TS38.133:"NR;Requirements for support of radio resource management".[14]3GPP TS22.168:"Earthquake and Tsunami Warning System(ETWS)requirements;Stage1".[15]3GPP TS22.268:"Public Warning System(PWS)Requirements".[16]3GPP TS38.410:"NG-RAN;NG general aspects and principles".[17]3GPP TS38.420:"NG-RAN;Xn general aspects and principles".[18]3GPP TS38.101:"NR;User Equipment(UE)radio transmission and reception".[19]3GPP TS22.261:"Service requirements for next generation new services and markets".[20]3GPP TS38.202:"NR;Physical layer services provided by the physical layer"[21]3GPP TS37.340:"NR;Multi-connectivity;Overall description;Stage-2".[22]3GPP TS23.502:"Procedures for the5G System;Stage2".[23]IETF RFC4960(2007-09):"Stream Control Transmission Protocol".[24]3GPP TS26.114:"Technical Specification Group Services and System Aspects;IP MultimediaSubsystem(IMS);Multimedia Telephony;Media handling and interaction".[25]Void.[26]3GPP TS38.413:"NG-RAN;NG Application Protocol(NGAP)".[27]IETF RFC3168(09/2001):"The Addition of Explicit Congestion Notification(ECN)to IP".[28]3GPP TS24.501:"NR;Non-Access-Stratum(NAS)protocol for5G System(5GS)".[29]3GPP TS36.331:"Evolved Universal Terrestrial Radio Access(E-UTRA);Radio ResourceControl(RRC);Protocol specification".3Abbreviations and Definitions3.1AbbreviationsFor the purposes of the present document,the abbreviations given in TR21.905[1],in TS36.300[2]and the following apply.An abbreviation defined in the present document takes precedence over the definition of the same abbreviation,if any,in TR21.905[1]and TS36.300[2].5GC5G Core Network5QI5G QoS IdentifierA-CSI Aperiodic CSIAKA Authentication and Key AgreementAMBR Aggregate Maximum Bit RateAMC Adaptive Modulation and CodingAMF Access and Mobility Management FunctionARP Allocation and Retention PriorityBA Bandwidth AdaptationBCH Broadcast ChannelBPSK Binary Phase Shift KeyingC-RNTI Cell RNTICBRA Contention Based Random AccessCCE Control Channel ElementCD-SSB Cell Defining SSBCFRA Contention Free Random AccessCMAS Commercial Mobile Alert ServiceCORESET Control Resource SetDFT Discrete Fourier TransformDCI Downlink Control InformationDL-SCH Downlink Shared ChannelDMRS Demodulation Reference SignalDRX Discontinuous ReceptionETWS Earthquake and Tsunami Warning SystemGFBR Guaranteed Flow Bit RateI-RNTI Inactive RNTIINT-RNTI Interruption RNTILDPC Low Density Parity CheckMDBV Maximum Data Burst VolumeMIB Master Information BlockMICO Mobile Initiated Connection OnlyMFBR Maximum Flow Bit RateMMTEL Multimedia telephonyMNO Mobile Network OperatorMU-MIMO Multi User MIMONCGI NR Cell Global IdentifierNCR Neighbour Cell RelationNCRT Neighbour Cell Relation TableNGAP NG Application ProtocolNR NR Radio AccessP-RNTI Paging RNTIPCH Paging ChannelPCI Physical Cell IdentifierPDCCH Physical Downlink Control ChannelPDSCH Physical Downlink Shared ChannelPO Paging OccasionPRACH Physical Random Access ChannelPRB Physical Resource BlockPRG Precoding Resource block GroupPSS Primary Synchronisation SignalPUCCH Physical Uplink Control ChannelPUSCH Physical Uplink Shared ChannelPWS Public Warning SystemQAM Quadrature Amplitude ModulationQFI QoS Flow IDQPSK Quadrature Phase Shift KeyingRA-RNTI Random Access RNTIRACH Random Access ChannelRANAC RAN-based Notification Area CodeREG Resource Element GroupRMSI Remaining Minimum SIRNA RAN-based Notification AreaRNAU RAN-based Notification Area UpdateRNTI Radio Network Temporary IdentifierRQA Reflective QoS AttributeRQoS Reflective Quality of ServiceRS Reference SignalRSRP Reference Signal Received PowerRSRQ Reference Signal Received QualitySD Slice DifferentiatorSDAP Service Data Adaptation ProtocolSFI-RNTI Slot Format Indication RNTISIB System Information BlockSI-RNTI System Information RNTISLA Service Level AgreementSMC Security Mode CommandSMF Session Management FunctionS-NSSAI Single Network Slice Selection Assistance Information SPS Semi-Persistent Scheduling SR Scheduling RequestSRS Sounding Reference SignalSS Synchronization SignalSSB SS/PBCH blockSSS Secondary Synchronisation SignalSST Slice/Service TypeSU-MIMO Single User MIMOSUL Supplementary UplinkTA Timing AdvanceTPC Transmit Power ControlUCI Uplink Control InformationUL-SCH Uplink Shared ChannelUPF User Plane FunctionURLLC Ultra-Reliable and Low Latency CommunicationsXn-C Xn-Control planeXn-U Xn-User planeXnAP Xn Application Protocol3.2DefinitionsFor the purposes of the present document,the terms and definitions given in TR21.905[1],in TS36.300[2]and the following apply.A term defined in the present document takes precedence over the definition of the same term,if any, in TR21.905[1]and TS36.300[2].Cell-Defining SSB:an SSB with an RMSI associated.CORESET#0:the control resource set for at least SIB1scheduling,can be configured either via MIB or via dedicated RRC signalling.gNB:node providing NR user plane and control plane protocol terminations towards the UE,and connected via the NG interface to the5GC.Intra-system Handover:Handover that does not involve a CN change(EPC or5GC).Inter-system Handover:Handover that involves a CN change(EPC or5GC).MSG1:preamble transmission of the random access procedure.MSG3:first scheduled transmission of the random access procedure.ng-eNB:node providing E-UTRA user plane and control plane protocol terminations towards the UE,and connected via the NG interface to the5GC.NG-C:control plane interface between NG-RAN and5GC.NG-U:user plane interface between NG-RAN and5GC.NG-RAN node:either a gNB or an ng-eNB.Numerology:corresponds to one subcarrier spacing in the frequency domain.By scaling a reference subcarrier spacing by an integer N,different numerologies can be defined.Xn:network interface between NG-RAN nodes.4Overall Architecture and Functional Split4.1Overall ArchitectureAn NG-RAN node is either:-a gNB,providing NR user plane and control plane protocol terminations towards the UE;or-an ng-eNB,providing E-UTRA user plane and control plane protocol terminations towards the UE.The gNBs and ng-eNBs are interconnected with each other by means of the Xn interface.The gNBs and ng-eNBs are also connected by means of the NG interfaces to the5GC,more specifically to the AMF(Access and Mobility Management Function)by means of the NG-C interface and to the UPF(User Plane Function)by means of the NG-U interface(see TS23.501[3]).NOTE:The architecture and the F1interface for a functional split are defined in TS38.401[4].The NG-RAN architecture is illustrated in Figure4.1-1below.Figure4.1-1:Overall Architecture4.2Functional SplitThe gNB and ng-eNB host the following functions:-Functions for Radio Resource Management:Radio Bearer Control,Radio Admission Control,Connection Mobility Control,Dynamic allocation of resources to UEs in both uplink anddownlink(scheduling);-IP header compression,encryption and integrity protection of data;-Selection of an AMF at UE attachment when no routing to an AMF can be determined from the information provided by the UE;-Routing of User Plane data towards UPF(s);-Routing of Control Plane information towards AMF;-Connection setup and release;-Scheduling and transmission of paging messages;-Scheduling and transmission of system broadcast information(originated from the AMF or OAM);-Measurement and measurement reporting configuration for mobility and scheduling;-Transport level packet marking in the uplink;-Session Management;-Support of Network Slicing;-QoS Flow management and mapping to data radio bearers;-Support of UEs in RRC_INACTIVE state;-Distribution function for NAS messages;-Radio access network sharing;-Dual Connectivity;-Tight interworking between NR and E-UTRA.The AMF hosts the following main functions(see TS23.501[3]):-NAS signalling termination;-NAS signalling security;-AS Security control;-Inter CN node signalling for mobility between3GPP access networks;-Idle mode UE Reachability(including control and execution of paging retransmission);-Registration Area management;-Support of intra-system and inter-system mobility;-Access Authentication;-Access Authorization including check of roaming rights;-Mobility management control(subscription and policies);-Support of Network Slicing;-SMF selection.The UPF hosts the following main functions(see TS23.501[3]):-Anchor point for Intra-/Inter-RAT mobility(when applicable);-External PDU session point of interconnect to Data Network;-Packet routing&forwarding-Packet inspection and User plane part of Policy rule enforcement;-Traffic usage reporting;-Uplink classifier to support routing traffic flows to a data network;-Branching point to support multi-homed PDU session;-QoS handling for user plane,e.g.packet filtering,gating,UL/DL rate enforcement;-Uplink Traffic verification(SDF to QoS flow mapping);-Downlink packet buffering and downlink data notification triggering.The Session Management function(SMF)hosts the following main functions(see TS23.501[3]): -Session Management;-UE IP address allocation and management;-Selection and control of UP function;-Configures traffic steering at UPF to route traffic to proper destination;-Control part of policy enforcement and QoS;-Downlink Data Notification.This is summarized on the figure below where yellow boxes depict the logical nodes and white boxes depict the main functions.Figure4.2-1:Functional Split between NG-RAN and5GC4.3Network Interfaces4.3.1NG Interface4.3.1.1NG User PlaneThe NG user plane interface(NG-U)is defined between the NG-RAN node and the UPF.The user plane protocol stack of the NG interface is shown on Figure4.3.1.1-1.The transport network layer is built on IP transport and GTP-U is used on top of UDP/IP to carry the user plane PDUs between the NG-RAN node and the UPF.Figure4.3.1.1-1:NG-U Protocol StackNG-U provides non-guaranteed delivery of user plane PDUs between the NG-RAN node and the UPF.Further details of NG-U can be found in TS38.410[16].4.3.1.2NG Control PlaneThe NG control plane interface(NG-C)is defined between the NG-RAN node and the AMF.The control plane protocol stack of the NG interface is shown on Figure4.3.1.2-1.The transport network layer is built on IP transport.For the reliable transport of signalling messages,SCTP is added on top of IP.The application layer signalling protocol is referred to as NGAP(NG Application Protocol).The SCTP layer provides guaranteed delivery of application layer messages.In the transport,IP layer point-to-point transmission is used to deliver the signalling PDUs.Figure4.3.1.2-1:NG-C Protocol StackNG-C provides the following functions:-NG interface management;-UE context management;-UE mobility management;-Transport of NAS messages;-Paging;-PDU Session Management;-Configuration Transfer;-Warning Message Transmission.Further details of NG-C can be found in TS38.410[16].4.3.2Xn Interface4.3.2.1Xn User PlaneThe Xn User plane(Xn-U)interface is defined between two NG-RAN nodes.The user plane protocol stack on the Xn interface is shown in Figure4.3.2.1-1.The transport network layer is built on IP transport and GTP-U is used on top of UDP/IP to carry the user plane PDUs.Figure4.3.2.1-1:Xn-U Protocol StackXn-U provides non-guaranteed delivery of user plane PDUs and supports the following functions: -Data forwarding;-Flow control.Further details of Xn-U can be found in TS38.420[17].4.3.2.2Xn Control PlaneThe Xn control plane interface(Xn-C)is defined between two NG-RAN nodes.The control plane protocol stack of the Xn interface is shown on Figure4.3.2.2-1.The transport network layer is built on SCTP on top of IP.The application layer signalling protocol is referred to as XnAP(Xn Application Protocol).The SCTP layer provides the guaranteed delivery of application layer messages.In the transport IP layer point-to-point transmission is used to deliver the signalling PDUs.Figure4.3.2.2-1:Xn-C Protocol StackThe Xn-C interface supports the following functions:-Xn interface management;-UE mobility management,including context transfer and RAN paging;-Dual connectivity.Further details of Xn-C can be found in TS38.420[17].4.4Radio Protocol Architecture4.4.1User PlaneThe figure below shows the protocol stack for the user plane,where SDAP,PDCP,RLC and MAC sublayers (terminated in gNB on the network side)perform the functions listed in subclause6.Figure4.4.1-1:User Plane Protocol Stack4.4.2Control PlaneThe figure below shows the protocol stack for the control plane,where:-PDCP,RLC and MAC sublayers(terminated in gNB on the network side)perform the functions listed in subclause6;-RRC(terminated in gNB on the network side)performs the functions listed in subclause7;-NAS control protocol(terminated in AMF on the network side)performs the functions listed in TS23.501[3]), for instance:authentication,mobility management,security control…Figure4.4.2-1:Control Plane Protocol Stack4.5Multi-Radio Dual ConnectivityNG-RAN supports Multi-Radio Dual Connectivity(MR-DC)operation whereby a UE in RRC_CONNECTED is configured to utilise radio resources provided by two distinct schedulers,located in two different NG-RAN nodes connected via a non-ideal backhaul,one providing NR access and the other one providing either E-UTRA or NR access. Further details of MR-DC operation can be found in TS37.340[21].5Physical Layer5.1Waveform,numerology and frame structureThe downlink transmission waveform is conventional OFDM using a cyclic prefix.The uplink transmission waveform is conventional OFDM using a cyclic prefix with a transform precoding function performing DFT spreading that can be disabled or enabled.Figure5.1-1:Transmitter block diagram for CP-OFDM with optional DFT-spreadingThe numerology is based on exponentially scalable sub-carrier spacing f=2µ×15kHz withµ={0,1,3,4}for PSS,SSS and PBCH andµ={0,1,2,3}for other channels.Normal CP is supported for all sub-carrier spacings,Extended CP is supported forµ=2.12consecutive sub-carriers form a Physical Resource Block(PRB).Up to275PRBs are supported on a carrier.Table5.1-1:Supported transmission numerologies.µ[kHz]f Cyclic prefix Supported for data Supported for synchµ=2?15015Normal Yes Yes130Normal Yes Yes260Normal,Extended Yes No3120Normal Yes Yes4240Normal No YesThe UE may be configured with one or more bandwidth parts on a given component carrier,of which only one can be active at a time,as described in subclauses7.8and6.10respectively.The active bandwidth part defines the UE's operating bandwidth within the cell's operating bandwidth.For initial access,and until the UE's configuration in a cell is received,initial bandwidth part detected from system information is used.Downlink and uplink transmissions are organized into frames with10ms duration,consisting of ten1ms subframes. Each frame is divided into two equally-sized half-frames of five subframes each.The slot duration is14symbols with Normal CP and12symbols with Extended CP,and scales in time as a function of the used sub-carrier spacing so that there is always an integer number of slots in a subframe. Timing Advance TA is used to adjust the uplink frame timing relative to the downlink frame timing.Figure5.1-2:Uplink-downlink timing relationOperation on both paired and unpaired spectrum is supported.5.2Downlink5.2.1Downlink transmission schemeA closed loop Demodulation Reference Signal(DMRS)based spatial multiplexing is supported for Physical Downlink Shared Channel(PDSCH).Up to8and12orthogonal DL DMRS ports are supported for type1and type2DMRS respectively.Up to8orthogonal DL DMRS ports per UE are supported for SU-MIMO and up to4orthogonal DL DMRS ports per UE are supported for MU-MIMO.The number of SU-MIMO code words is one for1-4layer transmissions and two for5-8layer transmissions.The DMRS and corresponding PDSCH are transmitted using the same precoding matrix and the UE does not need to know the precoding matrix to demodulate the transmission.The transmitter may use different precoder matrix for different parts of the transmission bandwidth,resulting in frequency selective precoding.The UE may also assume that the same precoding matrix is used across a set of Physical Resource Blocks(PRBs)denoted Precoding Resource Block Group(PRG).Transmission durations from2to14symbols in a slot is supported.Aggregation of multiple slots with Transport Block(TB)repetition is supported.5.2.2Physical-layer processing for physical downlink shared channelThe downlink physical-layer processing of transport channels consists of the following steps:-Transport block CRC attachment;-Code block segmentation and code block CRC attachment;-Channel coding:LDPC coding;-Physical-layer hybrid-ARQ processing;-Rate matching;-Scrambling;-Modulation:QPSK,16QAM,64QAM and256QAM;-Layer mapping;-Mapping to assigned resources and antenna ports.The UE may assume that at least one symbol with demodulation reference signal is present on each layer in which PDSCH is transmitted to a UE,and up to3additional DMRS can be configured by higher layers.Phase Tracking RS may be transmitted on additional symbols to aid receiver phase tracking.The DL-SCH physical layer model is described in TS38.202[20].5.2.3Physical downlink control channelsThe Physical Downlink Control Channel(PDCCH)can be used to schedule DL transmissions on PDSCH and UL transmissions on PUSCH,where the Downlink Control Information(DCI)on PDCCH includes: -Downlink assignments containing at least modulation and coding format,resource allocation,and hybrid-ARQ information related to DL-SCH;-Uplink scheduling grants containing at least modulation and coding format,resource allocation,and hybrid-ARQ information related to UL-SCH.In addition to scheduling,PDCCH can be used to for-Activation and deactivation of configured PUSCH transmission with configured grant;-Activation and deactivation of PDSCH semi-persistent transmission;。

WIRELESS COMMUNICATIONS AND MOBILE COMPUTINGput.2013;13:1587–1611 Published online11October2011in Wiley Online Library().DOI:10.1002/wcm.1203RESEARCH ARTICLEA survey of mobile cloud computing:architecture, applications,and approachesHoang T.Dinh,Chonho Lee,Dusit Niyato*and Ping WangSchool of Computer Engineering,Nanyang Technological University(NTU),SingaporeABSTRACTTogether with an explosive growth of the mobile applications and emerging of cloud computing concept,mobile cloud computing(MCC)has been introduced to be a potential technology for mobile services.MCC integrates the cloud com-puting into the mobile environment and overcomes obstacles related to the performance(e.g.,battery life,storage,and bandwidth),environment(e.g.,heterogeneity,scalability,and availability),and security(e.g.,reliability and privacy)dis-cussed in mobile computing.This paper gives a survey of MCC,which helps general readers have an overview of the MCC including the definition,architecture,and applications.The issues,existing solutions,and approaches are presented. In addition,the future research directions of MCC are discussed.Copyright©2011John Wiley&Sons,Ltd. KEYWORDSmobile cloud computing;offloading;mobile services*CorrespondenceDusit Niyato,School of Computer Engineering,Nanyang Technological University(NTU),Singapore.E-mail:dniyato@.sg1.INTRODUCTIONMobile devices(e.g.,smartphone and tablet PC)are increasingly becoming an essential part of human life as the most effective and convenient communication tools not bounded by time and place.Mobile users accumulate rich experience of various services from mobile applications (e.g.,iPhone apps and Google apps),which run on the devices and/or on remote servers via wireless networks. The rapid progress of mobile computing(MC)[1]becomes a powerful trend in the development of IT technology as well as commerce and industryfields.However,the mobile devices are facing many challenges in their resources(e.g., battery life,storage,and bandwidth)and communications (e.g.,mobility and security)[2].The limited resources significantly impede the improvement of service qualities. Cloud computing(CC)has been widely recognized as the next generation computing offers some advantages by allowing users to use infrastructure (e.g.,servers,networks,and storages),platforms(e.g.,mid-dleware services and operating systems),and softwares (e.g.,application programs)provided by cloud providers (e.g.,Google,Amazon,and Salesforce)at low cost.In addition,CC enables users to elastically utilize resources in an on-demand fashion.As a result,mobile applica-tions can be rapidly provisioned and released with the minimal management efforts or service provider’s interac-tions.With the explosion of mobile applications and the support of CC for a variety of services for mobile users, mobile cloud computing(MCC)is introduced as an inte-gration of CC into the mobile environment.MCC brings new types of services and facilities mobile users to take full advantages of CC.This paper presents a comprehensive survey on MCC. Section2provides a brief overview of MCC including defi-nition,architecture,and its advantages.Section3discusses the use of MCC in various applications.Then,Section4 presents several issues that arise in MCC and approaches to address the issues.Next,the future research directions are outlined in Section5.Finally,we summarize and conclude the survey in Section6.The list of acronyms appeared in this paper is given in Table I.2.OVERVIEW OF MOBILE CLOUD COMPUTINGThe term‘mobile cloud computing’was introduced not long after the concept of‘cloud computing’.It has been attracting the attentions of entrepreneurs as a profitable business option that reduces the development and run-ning cost of mobile applications,of mobile users as aCopyright©2011John Wiley&Sons,Ltd.1587A survey of mobile cloud computing H.T.Dinh et al.T able I.Acronyms4G Fourth GenerationAAA Authentication,Authorization,AccountingAPDV Application Protocol Data UnitAPI Application Programing InterfaceARM Advanced RISC MachineAV AntivirusB2B Business to BusinessB2C Business to CustomerBTS Base Transceiver StationCC Cloud ComputingCSP Cloud Service ProviderEC2Elastic Compute CloudGPS Global Positioning SystemHA Home AgentIaaS Infrastructure as a ServiceIA Integrated AuthenticatedID IdentifierIMERA French acronym for Mobile Interaction in Augmented Reality EnvironmentISP Internet Service ProviderIRNA Intelligent Radio Network AccessJME Java ME,a Java platformLBS Location Base ServiceLTE Long Term EvolutionLTS Location Trusted ServerMAUI Memory Arithmetic Unit and InterfaceMC Mobile ComputingMCC Mobile Cloud ComputingMDP Markov Decision ProcessMSC Mobile Service CloudP2P Peer-to-PeerPaaS Platform as a ServiceQoS Quality of ServiceRACE Resource-Aware Collaborative ExecutionREST Repretational State TransferRFS Random File SystemRTP Real-time Transport ProtocolS3Simple Storage ServiceSaaS Software as a ServiceTCC Truster Crypto CoprocessorURI Uniform Resource Identifiernew technology to achieve rich experience of a variety of mobile services at low cost,and of researchers as a promis-ing solution for green IT[3].This section provides an overview of MCC including definition,architecture,and advantages of MCC.2.1.What is mobile cloud computing?The MCC forum defines MCC as follows[4]:‘Mobile cloud computing at its simplest,refers to an infrastructure where both the data storage and data pro-cessing happen outside of the mobile device.Mobile cloud applications move the computing power and data storage away from mobile phones and into the cloud,bringing applications and MC to not just smartphone users but a much broader range of mobile subscribers’.Aepona[5]describes MCC as a new paradigm for mobile applications whereby the data processing and stor-age are moved from the mobile device to powerful and centralized computing platforms located in clouds.These centralized applications are then accessed over the wireless connection based on a thin native client or web browser on the mobile devices.Alternatively,MCC can be defined as a combination of mobile web and CC[6,7],which is the most popular tool for mobile users to access applications and services on the Internet.Briefly,MCC provides mobile users with the data pro-cessing and storage services in clouds.The mobile devicesput.2013;13:1587–1611©2011John Wiley&Sons,Ltd.DOI:10.1002/wcmH.T.Dinh et al.A survey of mobile cloud computingdo not need a powerful configuration(e.g.,CPU speed and memory capacity)because all the complicated computing modules can be processed in the clouds.2.2.Architectures of mobile cloud computingFrom the concept of MCC,the general architecture of MCC can be shown in Figure1.In Figure1,mobile devices are connected to the mobile networks via base stations (e.g.,base transceiver station,access point,or satellite) that establish and control the connections(air links)and functional interfaces between the networks and mobile devices.Mobile users’requests and information(e.g.,ID and location)are transmitted to the central processors that are connected to servers providing mobile network ser-vices.Here,mobile network operators can provide ser-vices to mobile users as authentication,authorization,and accounting based on the home agent and subscribers’data stored in databases.After that,the subscribers’requests are delivered to a cloud through the Internet.In the cloud, cloud controllers process the requests to provide mobile users with the corresponding cloud services.These ser-vices are developed with the concepts of utility computing, virtualization,and service-oriented architecture(e.g.,web, application,and database servers).The details of cloud architecture could be different in different contexts.For example,a four-layer architecture is explained in[8]to compare cloud computing with grid computing.Alternatively,a service-oriented architec-ture,called Aneka,is introduced to enable developers to applications with the supports of application programming interfaces(APIs)and multiple programming models[9].[10]presents an architecture for creating market-oriented clouds and[11]proposes an architecture for web-delivered business services.In this paper,we focus on a layered architecture of CC(Figure2). This architecture is commonly used to demonstrate the effectiveness of the CC model in terms of meeting the user’s requirements[12].Generally,a CC is a large-scale distributed network sys-tem implemented based on a number of servers in data centers.The cloud services are generally classified based on a layer concept(Figure2).In the upper layers of this paradigm,Infrastructure as a Service(IaaS),Platform as a Service(PaaS),and Software as a Service(SaaS)are stacked.Data centers layer.This layer provides the hardware facility and infrastructure for clouds.In data center layer,a number of servers are linked with high-speed networks to provide services for customers.Typically, data centers are built in less populated places,with a high power supply stability and a low risk of disaster. IaaS.Infrastructure as a Service is built on top of the data center layer.IaaS enables the provision of storage,hardware,servers,and networking compo-nents.The client typically pays on a per-use basis.Thus,clients can save cost as the payment is only based on how much resource they really use.Infras-tructure can be expanded or shrunk dynamically as needed.The examples of IaaS are Amazon Elastic Cloud Computing and Simple Storage Service(S3). PaaS.Platform as a Service offers an advanced inte-grated environment for building,testing,and deploy-ing custom applications.The examples of PaaSareFigure1.Mobile cloud computing architecture.put.2013;13:1587–1611©2011John Wiley&Sons,Ltd.1589 DOI:10.1002/wcmA survey of mobile cloud computing H.T.Dinh et al.Software as a Service (Microsoft’s Live Mesh)Platform as a Service (e.g., Google App engine, Microsoft Azure)Data centersInfrastructure as a Service (e.g., EC2, S3)Figure2.Service-oriented cloud computing architecture.Google App Engine,Microsoft Azure,and Amazon Map Reduce/Simple Storage Service.SaaS.Software as a Service supports a software dis-tribution with specific requirements.In this layer, the users can access an application and informa-tion remotely via the Internet and pay only for that they use.Salesforce is one of the pioneers in pro-viding this service model.Microsoft’s Live Mesh also allows sharingfiles and folders across multiple devices simultaneously.Although the CC architecture can be divided into four layers as shown in Figure2,it does not mean that the top layer must be built on the layer directly below it.For exam-ple,the SaaS application can be deployed directly on IaaS, instead of PaaS.Also,some services can be considered as a part of more than one layer.For example,data storage service can be viewed as either in IaaS or PaaS.Given this architectural model,the users can use the servicesflexibly and efficiently.2.3.Advantages of mobile cloudcomputingCloud computing is known to be a promising solution for MC because of many reasons(e.g.,mobility,communica-tion,and portability[13]).In the following,we describe how the cloud can be used to overcome obstacles in MC, thereby pointing out advantages of MCC.(1)Extending battery lifetime.Battery is one of themain concerns for mobile devices.Several solutionshave been proposed to enhance the CPU perfor-mance[14,15]and to manage the disk and screen inan intelligent manner[16,17]to reduce power con-sumption.However,these solutions require changesin the structure of mobile devices,or they requirea new hardware that results in an increase of costand may not be feasible for all mobile devices.Computation offloading technique is proposed withthe objective to migrate the large computations andcomplex processing from resource-limited devices(i.e.,mobile devices)to resourceful machines(i.e.,servers in clouds).This avoids taking a long applica-tion execution time on mobile devices which results in large amount of power consumption.Rudenko et al.[18]and Smailagic and Ettus[19]evaluate the effectiveness of offloading tech-niques through several experiments.The results demonstrate that the remote application execution can save energy significantly.Especially,Rudenko et al.[18]evaluates large-scale numerical com-putations and shows that up to45%of energy consumption can be reduced for large matrix calcu-lation.In addition,many mobile applications take advantages from task migration and remote pro-cessing.For example,offloading a compiler opti-mization for image processing[20]can reduce 41%for energy consumption of a mobile device.Also,using memory arithmetic unit and interface (MAUI)to migrate mobile game components[21] to servers in the cloud can save27%of energy consumption for computer games and45%for the chess game.(2)Improving data storage capacity and processingpower.Storage capacity is also a constraint for mobile devices.MCC is developed to enable mobile users to store/access the large data on the cloud through wireless networks.First example is the Amazon Simple Storage Service[22]which sup-portsfile storage service.Another example is Image Exchange which utilizes the large storage space in clouds for mobile users[23].This mobile photo sharing service enables mobile users to upload images to the clouds immediately after capturing.Users may access all images from any devices.With the cloud,the users can save considerable amount of energy and storage space on their mobile devices because all images are sent and processed on the clouds.Flicker[24]and ShoZu[25]are also the suc-cessful mobile photo sharing applications based on MCC.Facebook[26]is the most successful social network application today,and it is also a typical example of using cloud in sharing images.put.2013;13:1587–1611©2011John Wiley&Sons,Ltd.DOI:10.1002/wcmH.T.Dinh et al.A survey of mobile cloud computingMobile cloud computing also helps in reducingthe running cost for compute-intensive applicationsthat take long time and large amount of energywhen performed on the limited-resource devices.CC can efficiently support various tasks for datawarehousing,managing and synchronizing multi-ple documents online.For example,clouds can beused for transcoding[27],playing chess[21,28],or broadcasting multimedia services[29]to mobiledevices.In these cases,all the complex calcula-tions for transcoding or offering an optimal chessmove that take a long time when perform on mobiledevices will be processed efficiently on the cloud.Mobile applications also are not constrained by stor-age capacity on the devices because their data nowis stored on the cloud.(3)Improving reliability.Storing data or running appli-cations on clouds is an effective way to improvethe reliability because the data and application arestored and backed up on a number of computers.This reduces the chance of data and application loston the mobile devices.In addition,MCC can bedesigned as a comprehensive data security modelfor both service providers and users.For example,the cloud can be used to protect copyrighted digitalcontents(e.g.,video,clip,and music)from beingabused and unauthorized distribution[30].Also,thecloud can remotely provide to mobile users withsecurity services such as virus scanning,maliciouscode detection,and authentication[31].Also,suchcloud-based security services can make efficientuse of the collected record from different users toimprove the effectiveness of the services.In addition,MCC also inherits some advantages of clouds for mobile services as follows:Dynamic provisioning.Dynamic on-demand provi-sioning of resources on afine-grained,self-service basis is aflexible way for service providers and mobile users to run their applications without advanced reservation of resources.Scalability.The deployment of mobile applications can be performed and scaled to meet the unpredictable user demands due toflexible resource provisioning.Service providers can easily add and expand an appli-cation and service without or with little constraint on the resource usage.Multitenancy.Service providers(e.g.,network oper-ator and data center owner)can share the resources and costs to support a variety of applications and large number of users.Ease of integration.Multiple services from different service providers can be integrated easily through the cloud and Internet to meet the user demand.3.APPLICATIONS OF MOBILE CLOUD COMPUTINGMobile applications gain increasing share in a global mobile market.Various mobile applications have taken the advantages of MCC.In this section,some typical MCC applications are introduced.3.1.Mobile commerceMobile commerce(m-commerce)is a business model for commerce using mobile devices.The m-commerce applications generally fulfill some tasks that require mobility(e.g.,mobile transactions and payments,mobile messaging,and mobile ticketing).The m-commerce appli-cations can be classified into few classes includingfinance, advertising,and shopping(Table II).The m-commerce applications have to face various chal-lenges(e.g.,low network bandwidth,high complexity of mobile device configurations,and security).Therefore, m-commerce applications are integrated into CC environ-ment to address these issues.Yang et al.[32]proposes a3G E-commerce platform based on CC.This paradigm com-bines the advantages of both third generation(3G)network and CC to increase data processing speed and security level [33]based on public key infrastructure(PKI).The PKI mechanism uses an encryption-based access control and an over-encryption to ensure privacy of user’s access to the outsourced data.In[34],a4PL-A VE trading platform uti-lizes CC technology to enhance the security for users and improve the customer satisfaction,customer intimacy,and cost competitiveness.3.2.Mobile learningMobile learning(m-learning)is designed based on elec-tronic learning(e-learning)and mobility.However,tradi-tional m-learning applications have limitations in terms of high cost of devices and network,low network trans-mission rate,and limited educational resources[35–37].T able II.Application classes of m-commerce.Application classes Type ExamplesMobilefinancial applications B2C,B2B Banks,brokeragefirms,mobile-user feesMobile advertising B2C Sending custom made advertisements according to user’s physical location Mobile shopping B2C,B2B Locate/order certain products from a mobile terminalB2C,business to customer;B2B,business to businessput.2013;13:1587–1611©2011John Wiley&Sons,Ltd.1591 DOI:10.1002/wcmA survey of mobile cloud computing H.T.Dinh et al.Cloud-based m-learning applications are introduced to solve these limitations.For example,utilizing a cloud with the large storage capacity and powerful processing ability, the applications provide learners with much richer services in terms of data(information)size,faster processing speed, and longer battery life.Zhao et al.[38]presents the benefits of combining m-learning and CC to enhance the communication quality between students and teachers.In this case,a smartphone software based on the open source JavaME UI frame-work and Jaber for clients is used.Through a web site built on Google Apps Engine,students communicate with their teachers at anytime.Also,the teachers can obtain the information about student’s knowledge level of the course and can answer students’questions in a timely manner.In addition,a contextual m-learning system based on Mobile Interaction in Augmented Reality Environment platform [39]shows that a cloud-based m-learning system helps learners access learning resources remotely.Another example of MCC applications in learning is ‘Cornucopia’implemented for researches of undergradu-ate genetics students and‘plantations pathfinder’designed to supply information and provide a collaboration space for visitors when they visit the gardens[40].The purpose of the deployment of these applications is to help the students enhance their understanding about the appropriate design of MCC in supportingfield experiences.In[41],an educa-tion tool is developed based on CC to create a course about image/video processing.Through mobile phones,learn-ers can understand and compare different algorithms used in mobile applications(e.g.,deblurring,denoising,face detection,and image enhancement).3.3.Mobile healthcareThe purpose of applying MCC in medical applications is to minimize the limitations of traditional medical treat-ment(e.g.,small physical storage,security and privacy,and medical errors[42,43]).Mobile healthcare(m-healthcare) provides mobile users with convenient helps to access re-sources(e.g.,patient health records)easily and efficiently. Besides,m-healthcare offers hospitals and healthcare orga-nizations a variety of on-demand services on clouds rather than owning standalone applications on local servers. There are a few schemes of MCC applications in health-care.For example,[44]presentsfive main mobile health-care applications in the pervasive environment.Comprehensive health monitoring services enable patients to be monitored at anytime and anywhere through broadband wireless communications.Intelligent emergency management system can man-age and coordinate thefleet of emergency vehicles effectively and in time when receiving calls from accidents or incidents.Health-aware mobile devices detect pulse rate,blood pressure,and level of alcohol to alert healthcare emergency system.Pervasive access to healthcare information allows patients or healthcare providers to access the current and past medical information.Pervasive lifestyle incentive management can be used to pay healthcare expenses and manage other related charges automatically.Similarly,[45]proposes@HealthCloud,a prototype implementation of m-healthcare information manage-ment system based on CC and a mobile client running Android operating system(OS).This prototype presents three services utilizing the Amazon’s S3Cloud Storage Service to manage patient health records and medical images.Seamless connection to cloud storage allows users to retrieve,modify,and upload medical contents(e.g., medical images,patient health records,and biosig-nals)utilizing web services and a set of available APIs called Repretational State Transfer.Patient health record management system displays the information regarding patients’status,related biosignals,and image contents through application’s interface.Image viewing support allows the mobile users to decode the large imagefiles at different resolution levels given different network availability and quality. For practical system,a telemedicine homecare man-agement system[46]is implemented in Taiwan to moni-tor participants,especially for patients with hypertension and diabetes.The system monitors300participants and stores more than4736records of blood pressure and sugar measurement data on the cloud.When a participant per-forms blood glucose/pressure measurement via specialized equipment,the equipment can send the measured param-eters to the system automatically.Also,the participant can send parameters by SMS via their mobile devices. After that,the cloud will gather and analyze the infor-mation about the participant and return the results.The development of mobile healthcare clearly provides tremen-dous helps for the participants.However,the information to be collected and managed related to personal health is sensitive.Therefore,[47,48]propose solutions to protect the participant’s health information,thereby,increasing the privacy of the services.Although[47]uses peer-to-peer paradigm to federate clouds to address security issue,data protection,and ownership,the model in[48]provides secu-rity as a service on the cloud to protect mobile applications. Therefore,mobile health application providers and users will not have to worry about security issue because it is ensured by the security vendor.3.4.Mobile gamingMobile game(m-game)is a potential market generating revenues for service providers.M-game can completely offload game engine requiring large computing resourceput.2013;13:1587–1611©2011John Wiley&Sons,Ltd.DOI:10.1002/wcmH.T.Dinh et al.A survey of mobile cloud computing(e.g.,graphic rendering)to the server in the cloud,and gamers only interact with the screen interface on their devices.Li et al.[49]demonstrates that offloading(multimedia code)can save energy for mobile devices,thereby increas-ing game playing time on mobile devices.Cuervo et al.[21] proposes MAUI,a system that enablesfine-grained energy-aware offloading of mobile codes to a cloud.Also,a num-ber of experiments are conducted to evaluate the energy used for game applications with3G network and WiFi net-work.It is found that instead of offloading all codes to the cloud for processing,MAUI partitions the application codes at a runtime based on the costs of network com-munication and CPU on the mobile device to maximize energy savings given network connectivity.The results demonstrate that MAUI not only helps energy reduction significantly for mobile devices(i.e.,MAUI saves27% of energy usage for the video game and45%for chess), but also improves the performance of mobile applications (i.e.,the game’s refresh rate increases from6to13frames per second).Wang and Dey[50]presents a new cloud-based m-game using a rendering adaptation technique to dynami-cally adjust the game rendering parameters according to communication constraints and gamers’demands.The ren-dering adaptation technique mainly bases on the idea to reduce the number of objects in the display list because not all objects in the display list created by game engine are necessary for playing the game and scale the com-plexity of rendering operations.The objective is to max-imize the user experience given the communications and computing costs.3.5.Other practical applicationsA cloud becomes a useful tool to help mobile users share photos and video clips efficiently and tag their friends in popular social networks as Twitter and Facebook.MeLog [51]is an MCC application that enables mobile users to share real-time experience(e.g.,travel,shopping,and event)over clouds through an automatic blogging.The mobile users(e.g.,travelers)are supported by several cloud services such as guiding their trip,showing maps, recording itinerary,and storing images and video.Ye et al.[52]introduces a mobile locationing service allowing users to capture a short video clip about the surrounding buildings.The matching algorithm run on a cloud can use a large amount of information to search for a location of these buildings.Also,One Hour Trans-lation[53]provides an online translation service running on the cloud of Amazon Web Services.One Hour Transla-tion helps mobile users,especially foreign visitors,receive the information translated in their language through their mobile devices.A cloud becomes the most effective tool when mobile users require searching services(e.g.,searching informa-tion,location,images,voices,or video clips).Keyword-based searching.Pendyala and Holliday[54]proposes an intelligent mobile search modelusing semantic in which searching tasks will be per-formed on servers in a cloud.This model can analyze the meaning of a word,a phrase,or a complex multi-phase to produce the results efficiently and accurately.Lagerspetz and Tarkoma[55]presents an applica-tion using the cloud to perform data searching tasks for mobile gerspetz and Tarkoma[55]uses Dessy system[56]tofind the users’data,meta-data,and context information through desktop search(e.g.,indexing,query,and index term stemming,and search relevance ranking),and synchronization techniques.Voice-based searching.Fabbrizio et al.[57]pro-poses a search service via a speech recognition in which mobile users just talk to microphone on their devices rather than typing on keypads or touch-screens.Fabbrizio et al.[57]introduces the AT&T speech mashup model that utilizes web services and CC environment to meet the speech service demands of customers.This model optimizes the data trans-mission in a mobile network,reduces latency,and isflexible in integrating with other services.Several examples are demonstrated(e.g.,speak4it,iPizza,and JME local business search).Tag-based searching.Cai-Dong et al.[58]introducesa photo searching technique based on ontologicalsemantic tags.Mobile users search only recall param-eters that are tagged on images before such images are sent to a cloud.The cloud is used for storing and processing images for resource-limited devices.The current service is designed for the images stored on private CC environment.In the future,it is expected to expand for searching images in a public cloud environment.In addition,there are a mobile-cloud collaborative appli-cation[59]to detect traffic lights for the blind,a CC frame-work[60]to monitor different corners in a house through a mobile device,and some efforts which integrate cur-rent services(e.g.,BitTorrent,and Mobile Social Network) into the clouds as in[61,62].Thereby,we can recognize that MCC is probably a prevailing technology trend with numerous applications in the near future.4.ISSUES AND APPROACHES OF MOBILE CLOUD COMPUTINGAs discussed in the previous section,MCC has many advantages for mobile users and service providers.How-ever,because of the integration of two differentfields,that is,CC and mobile networks,MCC has to face many techni-cal challenges.This section lists several research issues in MCC,which are related to the mobile communication and CC.Then,the available solutions to address these issues are reviewed.put.2013;13:1587–1611©2011John Wiley&Sons,Ltd.1593 DOI:10.1002/wcm。

计算机无线网络前沿理论与技术课程报告关于下一代无线通信网络的详细综述（论文谷歌翻译）学院：计算机与信息技术学院专业：计算机科学与技术专业学号：姓名：教师：摘要相对比当前4G LTE网络。

下一代5G无线通信的愿景在于提供非常高的数据速率(通常为Gbps数量级)，极低的延迟，基站容量的增加以及用户感知的服务质量(QoS)的显着改善。

智能设备的不断增加，新兴的多媒体应用的引入，以及无线数据(多媒体)需求和使用的指数增长已经对现有蜂窝网络造成了重大负担。

5G无线系统，具有改进的数据速率，容量，延迟和QoS预期是当前蜂窝网络的大多数问题的灵丹妙药。

在本次调查中，我们对5G网络的无线演进做了详尽的回顾。

我们首先讨论与无线接入网(RAN)设计相关的新架构变化，包括空中接口，智能天线，云和异构RAN。

随后，我们对基础的新型毫米波物理层技术进行深入调查，包括新的信道模型估计，定向天线设计，波束成形算法和大规模MIMO技术。

接下来，讨论有效支持这个新物理层所需的MAC层协议和复用方案的细节。

我们还研究了杀手级应用程序，被认为是5G背后的主要驱动力。

为了了解改进的用户体验，我们提供与5G演进相关的新的QoS，QoE和SON功能的亮点。

为了减少增加的网络能耗和运营成本，我们对能源意识和成本效率进行了详细审查。

因为了解5G实施的当前状态对于其最终的商业化是重要的，我们还讨论相关的现场试验，驱动测试和模拟实验。

最后，我们指出现有的主要研究问题，并确定未来的研究方向。

关键字：5G毫米波波束成型信道模型 C-RANSDNHetNets大规模MIMO，SDMA，IDMA，D2D，M2M，IoT，QoE，SON，可持续性，实验1.引言移动无线通信始于第一代，纯语音系统已经有几十年了。

在过去几十年中，世界已经目睹了移动无线通信逐渐向第二，第三和第四代无线网络演进的趋势。

引入数字调制，有效的频率复用，基于分组的因特网的渗透以及诸如WCDMA，OFDMA，MIMO，HARQ等物理层技术的快速发展已经对这种逐渐演进做出了重大贡献。

Mobile Cloud Computing and Applications Chengzhong Xu【期刊名称】《《中兴通讯技术（英文版）》》【年(卷),期】2011(009)001【总页数】1页(P3)【作者】Chengzhong Xu【作者单位】【正文语种】中文In 2010,cloud computing gained momentum.Cloud computing is a model for real-time,on-demand,pay-for-use network access to a shared pool of configurable computing and storage resources.It has matured from a promising business concept to a working reality in both the private and public IT sectors.The ernment,for example,has requested all its agencies to evaluate cloud computing alternatives as part of their budget submissions for new IT investment.In recent years we have also witnessed the rapid growth of mobile applications due to the increasing popularity of smartphones and ubiquity of wireless access.Cloud computing fuels innovation in mobile computing and opens new pathways between mobile devices(where an application is launched)and the infrastructure(where data is stored andprocessed).Because mobile devices have intrinsic storage,processing,and battery power constraints,mobile applications often hit a performance wall.Unlimited computing and storage resources offered by cloud computing can help break through this wall and turn the problem into a vast opportunity for the growth of mobile computing.According to the latest study from Juniper Research,the market for cloud-based mobile applications is expected to grow 88%annually and reach$9.5 billion by 2014.To a typical mobile user,a mobile application driven by the cloud should look and feel just like any native mobile applications installed and run in their mobile device.There are already some well-known cloud-based mobile applications;for example,Google’s Gmail for iPhone and Cisco’s WebEx on iPad.These are largely run as Software-as-a-Service(SaaS),in which a cloud provider’s applications are deployed and run in the cloud and can be accessed by users.In general,cloud computing goes beyond the SaaS model by offering computing and storage Infrastructure as a Service(IaaS)or application development Platform as a Service(PaaS).Each cloud service model has proved efficacious in desktopcomputing.However,the benefits of IaaS and PaaS in mobile cloud computing have not been fully exploited.This special issue ofZTE Communicationsdiscusses related issues in mobile cloud computing.The purpose is to provide an overview of this cutting edge field and to describe its development,trends,challenges,and current practices.Papers have been included that cover a broad spectrum ofinteresting topics,including mobile cloud computing architectures,mobile search and data management,energy management and sustainability,privacy and security,mobile social networks,and novel cloud-assisted smartphone applications.In the paper,“A Survey of Mobile Cloud Computing,”Fan et al.class ify mobile cloud computing systems.Two representative systems,Hyrax and Cloudlet,are discussed in detail.In their paper“Mirroring Smartphones for Good:A Feasibility Study,”Zhao et al.propose a framework that keeps a mirror for each smartphone on a computing infrastructure in the telecom network.In this framework,some computational workload is offloaded from a smartphone to its mirror.They demonstrate the efficacy of the framework in data caching applications and antivirus scanning services.“A Cloud-Based Virtualized Execution Environment for Mobile Applications,”by Hung et al.presents a cloud-based virtualized execution environment framework for mobile applications,with a focus on schemes for migrating applications and synchronizing data between execution environments.Performance and power saving issues involved in application migration are also discussed.In“Building a Platform to Bridge Low End Mobile Phones and Cloud Computing Services,”Tso et al.propose a Thumb-in-Cloud platform to break the performance wall in low-end mobile phones.The platform consists of virtual machines that are deployed in low-end phones for execution of mobile applications.It also consists of Thumb gateways that tailor cloud services by reformatting and compressing the service conten t to fit into the phone’s profile.Zhang et al.in“WiFace:A Secure Geosocial Networking System Using Wi-Fi Based Multihop MANET,”present a geosocial networking system running on a Wi-Fi based multihop ad hoc network platform for personal mobile devices.The system allows users to access cloud services in environments with or without networking infrastructure or GPS modules.In“A Case for Cloud-Based Mobile Search,”Gao et al.design an Internet search case for cloud-based mobile applications.Searches launched in a mobile device invoke a cloud-based search engine to fulfill the tasks.Key enabling technologies are discussed.“An On-Demand Security Mechanism for Cloud-Based Telecommunications Services,”by Lin et al.investigates the security issues in cloud computing and a security model is proposed based on a security domain division concept.This helps provide dynamic,on-demand,and differentiated protection for services.I am grateful to the authors who submitted for this special issue and to the reviewers who spent their valuable time to provide constructive feedback.I hope that you find this special issue interesting and useful.。

Summary from RAN#78Outline 5G NR aspectsHandling of new WI/SI proposals LTE aspectsCall for a 5G workshop5G NR aspectsNon-Standalone 5G NR standards completed !Focus on essential functionalityIn Q1: RAN1 shall continue to focus on stabilizing basic and essential functionality for the scope of the December drop that was defined at RAN#77 in RP-172108, with two additions:•Scope for URLLC work for Rel-15 in H1 for the June drop endorsed in RP-172817•For NR-NR CA: finalization of the work to enable up to 2 different numerologies within the same PUCCH group (PUCCH sent on the CC with smaller SCS) in RAN1 in Q1, and in RAN4 (Core) for Q2, for the December drop.•Note: Situation to be re-assessed at RAN#79 in MarchRAN2 shall focus on closing the open issues for Option-3, and on commencing specification work for the essential components of Option-2Handling of Study Items in 2018 Measures to maximize meeting time available for Release-15 NR in H1/2018:Conclusion: Work on NR Study Items led by RAN1 or RAN2 shall be limitedto only one of the WG meetings in Q1, and limited to max. 1 TU each•The revised TU allocation for SIs is endorsed in RP-172805, RP-172782Conclusion-bis: Potential approval of any new proposed SI/WI shall be targeted to June/2018 at the earliest•This implies to all new RAN1, RAN2, RAN3, RAN4 proposals for both LTE and NR•Continuation of an existing NR SI to another SI might be possible even before June/2018•Continuation of an existing LTE SI to a WI/SI might be possible even before June/2018•New LTE WI proposals targeting Release 15 are to be discussed and decided case-by-caseArchitecture optionsIt is recognized that all architecture options remain within the scope of the NR WID (completion target: June/2018) Conclusion:•Until March/2018 WGs shall prioritize Option-3 stabilization (only essential corrections allowed), and on Option-2 specification work•NR-NR DC is within the scope of the work, but needs basic Option-2 functionalities to stabilize first NR-NR DC to commence in Q2•For Option-4, Option-7x: commence work once Option-2 and Option-3 are stabilized•Check the progress in March, and adjust plans/measures if necessaryRAN ArchitectureControl plane – User plane (CP –UP) split•Following the conclusion of the SI, RAN approved a new WID to commence with normative work for Release 15CU-DU Lower Layer split•TR approved, but no consensus on how and whether to continue the work•It was concluded to put the work on hold in RAN3 in Q1, and re-check the situation at RAN#79 (March/2018)Resolution on contentious itemsNR UE feature categorization, endorsed guidance in RP-172816 Mandatory 4Rx, conclusions in RP-172788Mandatory channel bandwidth aspects, conclusions in RP-172832UE power sharing aspects, conclusions in RP-172833NR UE categories, RAN email discussion will be conducted as described in RP-172757Administrative measuresAd-hoc meetings in July 2018 –Conclusion:•RAN1 AH in July is cancelled•RAN2 and RAN3 July AH confirmed•RAN4 July AH confirmed, but scope restricted to LTE/NR performance work only •Freeze 2018 meeting calendar as per the above, no new ad-hoc meetings!Ad-hoc meetings in 2019 –Conclusion:•Plan for 6 WG meetings for 2019, plan work accordingly (SI/WI approvals, etc…)•Remove RAN2, RAN3, RAN4 January and July ad-hocs from 3GPP calendar •Decide RAN1 January and July AH in June/2018, mark these as TBC for now Number of parallel sessions to be reduced in RAN1 from Q3/2018 onwards •Reduction in overall TU numbers (26→21 for NR, 17→14 for LTE)WGs are reminded about the PCG guidance on working hoursIMT2020 submissionCalibration for self-evaluation•Good progress, but more time is needed to complete the work Email discussion to continue until Feb/2018Initial description template•Initial Description Template for ITU-R submission is complete, LTI containing the template was sent to ITU-R following TSG-SA approvalStudy on 6 GHz for LTE and NR New Study Item was approved to investigate the existing regulatory framework in different regions for the 5.925-7.125 GHz band•The study covers the regulation for both the unlicensed and licensed use for this band The Study will be conducted in RAN plenary, mostly on the email reflector Planned completion date of the study: RAN#80 (June/2018)Handling of new WI/SIproposalsGeneral PrinciplesPrimary focus to be put on ensuring proper Objectives&Scope that correspond to true market needs Real Time Unit estimates to be included that are ‘signed off’ by the lead WG ChairmanProposed new WI/SI shall omit Rapporteur information, the Supporting Companies information, and the Lead WG information•Lead WG information and Supporting Companies to be filled in upon full stabilization of the Objectives&Scope•Rapporteur information to be filled in upon approval of W I/SIRole of and expectation towards the eventual Rapporteur•To serve as a neutral facilitator of the work•Not represent any company proposal or position for the WI/SI•Organize end ensure necessary cross-WG correspondence•Accurate and honest status reporting (open issues, TUs, etc…)•Strictly restrict the number of Rapporteurs for a WI/SI to a single personRapporteurship does not in any way represent a company’s leadership or the amount of innovation of a company for a certain WI/SI!All non-spectrum and non-testing WI/SI proposals to comply withNext Steps for Rel16 proposalsWork areas with multiple proposals at RAN#78 to be consolidated led by a Moderator over the RAN_Drafts exploder:•MIMO (NR & LTE), moderator: Samsung•NR Voice (including fallback), moderator: Huawei•IoT / eMTC evolution (LTE & NR), moderator: Ericsson•Broadcast (NR & LTE), moderator: Qualcomm•NR V2X, moderator: Vodafone•NR Positioning, moderator: Intel•NR flexible duplex, moderator: LG•NR Power Consumption, moderator: CATT (for the standalone aspects start after March)•NR URLLC Enhancements, moderator: Nokia (to be started after March)•NR Mobility, moderator: Intel (to be started after March)•Other miscellaneous NR enhancements/leftovers, moderator: Docomo•Note: individual SI/WI is needed for each individual item, i.e. no umbrella WI/SI!Other individual company proposals are also encouraged to be further developed on the RAN_Drafts exploderPractical Steps until June/2018Both the individual as well as the consolidated WI/SI proposals are encouraged to be further developed over the RAN_Drafts reflectorRole of the Moderator for consolidating the new work areas:•To serve as a neutral facilitator for the consolidation of the new work area into SI(s) and WI(s)•Not represent any company proposal or position during consolidationBeing a Moderator does not in any way represent a company’s leadership or the amount of innovation of a company for the work areaGoals for moderation:•Determination of a core set of objectives carrying support of a wide majority•Capturing other objectives with scattered support in []•Determining TUs for all potential objectives•Next checkpoint at RAN#79 (March/2018): moderator to submit summaries where applicableTSG-RAN to approve a set of new SIs/WIs at RAN#80 (June/2018)•This set will be a subset of all consolidated and individual proposalsLTE aspectsLTE ASN.1 freeze in March/2018In accordance with earlier decisions, it is confirmed that For LTE: The March/2018 ASN.1 freeze contains functions essential for NR NSA Option-3 family only, and does not contain any other Rel-15 LTE featureNumber of Radio Bearers•RAN approved a new WID to increase the maximum number of Radio Bearers a UE can establish to 15, see RP-172835•The WID is scheduled to be completed by June/2018, in time for Release-15•RAN assumes the corresponding core architecture&protocol parts to also complete in Release 15Low Latency for IMT2020•RAN decided to task RAN2 to specify a solution within Release-15 to reduce control plane latency so that IMT2020 requirements can be met•It is also endorsed for RAN2 to address the 0ms latency requirement as per RP- 172807LTE URLLC•Scope of the WID enhanced to enable the network to provide timing information at high granularityLight Connection•RAN decided to put the WID on LTE Light Connection on hold in accordance with SA decision•Topic to be re-addressed in June together with all other Release-16 proposals Support of Aerial Vehicles•New WID approved to optimize mobility and power control aspects to enable better support of aerial vehicles in LTE, see RP-172826Call for a 5G workshopBackground3GPP presented its plans for the submission of “5G” for inclusion in IMT-2020 during the ITU-R WP5D meeting in October 2017.At the end of the workshop a request was raised to organize a meeting between 3GPP and Evaluation Groups to provide an insight on the technology and ensure alignment of simulation scenarios.Possible dates are to be evaluated, but likely after the conclusion of Rel-15 Self Evaluation (September 2018).Workshop ScopeOrganize a 3GPP Workshop on “5G” in 2018• 1 ½ day workshop•From October 24th, 13:00 to October 25th, 17:00•Tentative host: European Commission in Bruxelles (pending confirmation)Target audience: Independent Evaluation Groups , Regulators, Administrations, Verticals Scope:•Present to Independent Evaluation Groups 3GPP’s IMT2020 submission to WP5D in October •Provide ins ights to 3GPP’s “5G” technologyProposed agenda: (Details TBD in later stage)•Specific technical features of the “5G” proposal•Submission templates•Description characteristics template, link budget template, and compliance templates •Self-Evaluation results (including simulation assumptions and calibration)•Anticipations on the final submission with Rel 15 and Rel 16 contentsThank You !。

新视角解读Cloud、SDN和NFV作者：李林泽来源：《科技风》2022年第29期摘要：本文围绕目前新型信息和通信技术（下文简称ICT）——云计算（Cloud Computing，下文或简称云）、软件定义网络（Software Defined Network，下文简称SDN）和网络功能虚拟化（Network Function Virtualization，下文简称NFV），追根溯源从三者各自的国际标准入手，并结合现网实际应用情况，简要解读这三种技术的作用特征与相互关系，然后从有机整体的视角分析三者之间的区别和联系，力求搭建一个清晰的新一代网络技术架构。

关键词：云计算；软件定义网络；网络功能虚拟化；网络可编程；ICT新技术当前网络技术发展的速度已经远远超出人们在半个世纪以前对网络的认知，5G网络建设的提速更进一步加速了从传统网络建设向可编程电信网的演进，其中涉及三种重要的关键技术——云计算、SDN和NFV，这三者在实现上有很多相似之处却又互为区别，功能上有关联之处却又可独立部署运维，一方面，三者都是IT（信息技术）和CT（通信技术）的融合体，三者都是网络可编程的典型代表，三者都可在同一个通信网络中融合组网，甚至可以通过三者之间的高度融合来实现进一步网络功能增强；另一方面，三者又有各自独特的应用场景，且由不同国际组织进行标准的主导。

虽然很多技术论文中对三者的应用屡有介绍，但却很少清晰地、有深度地从国际标准中对比剖析三者之间的联系并界定彼此的技术区别，在实际应用时让ICT 从业者备感困惑，犹如雾里看花。

在ICT领域所有厂家均遵循的权威规范是国际标准，故本文选择从这三种ICT技术各自主流的国际标准入手，并结合现网通行的实际行业应用简要解读国际标准中关于这三者的作用特征，以及在国际标准中提及的关于三种技术的交互场景，最后采用经典OSI（开放系统互联）模型进行功能映射分析，从而清晰还原这三种ICT新技术的本来面目。