PROPRIETARY RIGHTS STATEMENT This document contains information, which is proprietary to the 5G-Enhance Consortium. Research and Innovation Action 5G-Enhance 5G Enhanced Mobile Broadband Access Networks in Crowded Environments D2.2 – Unified Technical Requirements and Specification Contractual Delivery Date: 30-06-2019 Actual Delivery Date: 28-06-2019 Work Package WP2 - Unified use cases, trial scenario, and specifications between EU and Japan (RTD) Responsible Beneficiary: TUAT Contributing Beneficiaries: Accelleran, UOULU, VTT, FHG, NICT, TUAT, UEC, CATV Dissemination Level: Public Version: V12
Transcript
PROPRIETARY RIGHTS STATEMENTThis document contains information, which is proprietary to the 5G-Enhance Consortium.
Research and Innovation Action
5G-Enhance5G Enhanced Mobile Broadband Access Networks in
Crowded Environments
D2.2 – Unified Technical Requirements and Specification
Contractual Delivery Date: 30-06-2019Actual Delivery Date: 28-06-2019Work Package WP2 - Unified use cases, trial scenario, and specifications
between EU and Japan (RTD)Responsible Beneficiary: TUATContributing Beneficiaries: Accelleran, UOULU, VTT, FHG, NICT, TUAT, UEC, CATV
Dissemination Level: PublicVersion: V12
PROPRIETARY RIGHTS STATEMENTThis document contains information, which is proprietary to the 5G-Enhance Consortium.
This project has received funding from the European Union’s Horizon 2020 research andinnovation programme under grant agreement No 815056.
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Document Information
Document ID: D2.2Version Date: 28-06-2019Total Number of Pages: 45Abstract: This document investigates the 5G-Enhance trials technical
requirements and specifications. Also, it outlines the trialsarchitecture, utilized technologies, configurations, setup andevaluation procedure.
Keywords: 5G-Enhance, use cases, large scale trials, radio accesstechnologies (RAT), eMBB, micro-operator, multi-connectivity,vRAN
Version Date CommentsV01 07-05-2019 The first contentsV02 24-05-2019 VTT contributionV03 09-06-2019 Trial 1 description is updatedV04 10-06-2019 Trial 2 description is updatedV05 11-06-2019 Further updates based on teleconference meetingV06 12-06-2019 Editorial work, referencesV11 25-06-2019 Reviewers' comments are addressed, version ready for PMT approvalV12 28-06-2019 Final version
The objective of D2.2 entitled “Unified technical requirements and specifications”, is to specifyin detail the 5G-Enhance system requirements, specifications, architectures and usedtechnologies that will be later implemented in the trials. D2.2 aims to answer an importantquestion of how big the trials need to be scaled to from a system designer point of view.Additionally, a survey of 5G networks and categorization use cases and how the trials arealigned with them. Also, a review of system architecture, used technologies, incorporatedhardware devices, expected results, target KPI and a time plan for the trials is provided.The first trial is a live 3D AR streaming for real-time surgery. This demo requires a high datarate with a high user density, stringent delay constraint and slow/limited mobility.The second trial is a live ad-hoc outdoor sport event. This demo requires high data rates witha massive number of users and medium/high mobility
Several technologies have been developed for 5G-Enhance which will have a significantimpact on improving legacy solutions in dense eMBB scenarios. 5G-Enhance is built over twokey components, namely flexible and scalable network design and implementation andenhanced spectrum resource management. The technologies involved include spectrummanagement, micro-operator, network management and multi-connectivity.
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List of tables
Table 1 . 5G PPP KPIs and 5G-Enhance contributions ........................................................18Table 2 . Use case mapping. ................................................................................................19Table 3 . Incorporated technologies for 5G-Enhance. ...........................................................19
List of figures
Figure 1. ITU IMT2020 use cases and initial 5G deployment position [Mediatek_2018]. .......16Figure 2. 5G use case categories definition for broadband access [NGMN_2015]. ..............17Figure 3. 5G-Enhance trials main characteristics. .................................................................18Figure 4 .5GTN network architecture. ...................................................................................20Figure 5. Trial 1 network. ......................................................................................................21Figure 6. Multi-connectivity architecture................................................................................22Figure 7. Illustration of a virtualized RAN. .............................................................................24Figure 8. Illustration of multi-connectivity by using Accelleran vRAN cluster controller platform. .............................................................................................................................................24Figure 9. Trial 2 system architecture. ....................................................................................26Figure 10. Trial 2 contributing technologies. .........................................................................28Figure 11. Spectrum measurement system. .........................................................................30Figure 12. Signal processing for spectrum measurement. ....................................................30Figure 13. System structure of spectrum resource management based on spectrum database. .............................................................................................................................................31Figure 14 (a) Trial 1 hardware architecture in Operating Theatre..........................................32Figure 14 (b) Trial 1 hardware architecture at Student Theatre. ............................................33Figure 15. System configuration for spectrum sharing. .........................................................35Figure 16. Example of reconfiguration for adaptive spectrum sharing. ..................................36Figure 17. System configuration for spectrum sharing. .........................................................38
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Table of Contents
List of tables ............................................................................................................. 6
List of figures ............................................................................................................ 6
1. Introduction ..................................................................................................... 111.1 Purpose of the document ...................................................................................111.2 Structure of the document .................................................................................11
3.3 eMBB in 5G ..........................................................................................................163.4 Mapping among technologies, trials and use cases ........................................17
4. 5G-Enhance Trials systems architecture ...................................................... 194.1 5GTN network architecture ................................................................................204.2 Trial 1 Main Technologies ..................................................................................234.3 Open issues for Trial 1 .......................................................................................254.4 Trial 2 ...................................................................................................................25
4.4.1 System architecture ..........................................................................................254.4.2 Main technologies .............................................................................................27
5. Trials hardware setup and trial procedure .................................................... 315.1 Trial 1 setup and evaluation scenarios ..............................................................32
5.1.1 System configuration .........................................................................................325.1.2 Evaluation procedure .......................................................................................335.1.3 Expected results................................................................................................34
5.2 Trial 2 evaluation scenarios ...............................................................................355.2.1 Spectrum sharing ..............................................................................................355.2.2 Multi-link transmission of high-data-rate uplink video stream .............................38
6. Time plan and partners roles.......................................................................... 406.1 Time plan and availability ...................................................................................40
Term Description3GPP 3rd generation partnership project5G 5th generation wireless systems5G PPP the 5G infrastructure public private partnership5GTN 5G test networkAP access pointAPI application programming interfaceAR/VR augmented reality / virtual realityATSSS access traffic steering switching and splittingBS base stationCQI channel quality indicatorCWC center for wireless communicationDL downlinkDTX discontinuous transmissioneMBB enhanced mobile broadbandeMBMS evolved multimedia broadcast multicast service
EPC evolved packet coreHD high definitionIoT Internet of thingsITU-R international telecommunication union radio communication sectorKPI key performance indicatorLoRA long range [access network]LTE long term evolutionMC multi-connectivityMEC multi-access edge computingMME mobility management entitymMTC massive machine type communicationMPTCP multipath transmission control protocolNR new radioNFV network functions virtualizationPLMN public land mobile networkPU positive unlabeled learningRAT radio access technologyRRU remote radio unitQoS/QoE quality of service / quality of experienceQUIC quick UDP internet connectionsRNC radio network controllerRSRP reference signal received powerRSRQ reference signal received qualityRAN radio access network
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RSSI received signal strength indicatorSDR software defined radioSIM subcarrier index modulated [signal]SNR signal-to-noise ratioTDD time division duplexinguO micro operatorUE user equipmentUL uplinkURLLC ultra-reliable low-latency communicationVR virtual realityvRAN virtual RAN
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1.Introduction
The ITU-R defined three main usage cases for 5G, one of them is eMBB. The definition ofeMBB covers two scenarios: wide-area coverage and hotspot one. Each of them has a differentrequirement. The hotspot case includes high user densities in confined areas and requiresvery high traffic capacity and user data rates, while the requirement for mobility is low. For thewide-area coverage case, seamless coverage, high data rate and medium to high mobility aredesired [ITU-R_2015].The 5G-Enhance project main targets are two large scale demonstrations in EU and Japan.The first demonstration is a multiple angle camera real-time HD surgery streaming toparticipants in either a class or remote places. The second demonstration is HD live multipleangle cameras streaming of race course which requires wide-area coverage case. The twodemonstrations cover both eMBB use cases and aim to improve on current solutions andmethods by providing flexible and scalable network design and enhanced spectrum resourcemanagement.
1.1 Purpose of the documentThis document summarizes the outcome of activities performed in Task 2.2: Unified technicalrequirements and specifications and aims to specify in detail the 5G-Enhance systemrequirements, specifications, architectures and used technologies that will be laterimplemented in project trials. The topics addressed in this document include:
· One of the key aspects for the project success is the specification of how large the twotrials are required to be scaled to, taking into consideration system level developersview.
· Describe the techniques and technologies which will be incorporated in both trials andhow they improve on the current 4G/5G techniques.
· A detailed description of the trials’ architecture, hardware setup, configurations andrequired equipment.
· Setting a time plan for the rest of the project and every partner involvement in fulfillingthe deliverables.
· The identification of both the expected results and the target KPIs that will be validatedlater during the functional tests and trials.
· This document is the second deliverable of the 5G-Enhance project for WP2; hence itprovides a brief overview of the project, including trials description, architecture,configuration and setup. The considered technologies in the 5G-Enhance project whichwill improve on existing technologies and go beyond them. Time plan and target KPI ofthe trials.
· Open issues described in this documentation will be discussed in D2.3 Use case pilotplanning report.
1.2 Structure of the documentThe structure of this document
· Section 2: provides a brief description for both trials, live surgery streaming and sportad-hoc.
· Section 3: describes the technical requirements for the trials. The use case mappingbetween 5G use case families and project specific use cases, the target KPI.
· Section 4: first concerns with trials architecture, second defines key technologiesutilized in the two trials.
· Section 5: defines the trials configurations, hardware setup and procedure. Alsoprovides with essential information on how large scale the trials should be implementedand expected results.
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· Section 6: outlines the project time plan, methods to maximize the project impact andoutlines every partner role and involvement.
· Section 7: summarizes and concludes the main findings of the performed work in Task2.2
2.Trials Outline
2.1 Trials OutlineThe core of 5G-Enhance project is the performance evaluation of large-scale trials focusing oneMBB and spectrum/network sharing in both EU and Japan.In this section, a brief description to the two trials will be provided, emphasizing on thedemonstration of the advantages of the developed technologies in 5G-Enhance to eMBBscenario for both indoor environment (Trial 1) and outdoor environment (Trial 2).
2.1.1 Trial 1 OutlineTrial 1 is focused on demonstrating advantages of the technologies developed within 5G-Enhance project for eMBB scenario in an indoor environment with high density users and highdata rate requirement.
This demonstration covers a scenario in which a live video from hospital operating room isstreamed to the remotely located medical students or consultants, using the 5G network.Specifically, a hospital environment in Oulu, Finland, is selected for HD multi-angle live videostreaming of an operation using the local 5G wireless network, where students/participantscan watch the stream. The live streaming demonstration includes multiple remote controlled2D and 3D cameras with the required real time video stream rendering. It also includes varioussensor elements to monitor the physiology of the patient being operated. The demonstrationincorporates AR/VR enabled glasses/goggles or helmets with role identifications. Theintegration of AR/VR and (IoT sensors would have an essential impact on enriching thelearning process for students by providing an opportunity to learn from real case scenarios.Students can be in either a group (class room/theatre room) or individually (remote places).Moreover, a real-time 3D surgery stream can enable remote consultancy, by which theadvice/feedback of remotely located expertise could be collected as the operation isprogressing.The goal of this trial is to demonstrate how technologies developed in WP3 of the 5G-Enhanceproject contribute to improve user experience in eMBB scenario in an indoor environment witha high density of users. WP3 focuses on the following technologies:· WP3/T3.1: 5G-Enhance ARAT: Advance RAT architecture definition.· WP3/T3.2: 5G- Enhance ARAT: Interference mitigation techniques for local 5G networks
with dynamic TDD.· WP3/T3.3: 5G-Enhance ARAT: Multi-connectivity technique.
2.1.2 Trial 2 Outline
Trial 2 is focused on demonstrating advantages of the technologies developed within 5G-Enhance project for eMBB scenario in outdoor environment with high density of users requiringhigh data rates within rural space (i.e. the density of users is not continuous enough to be ableto economically sustain a comprehensive wide area operator network).Ehime bicycle race is selected as an event where expected scenario Trial conditions will bemet including a high concentration of users for a limited duration of time (i.e. the trial time). In
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addition to regular eMBB scenario applications, some of these users will generate high datarate video content from multiple cameras mounted on race participant bicycles. The generatedvideo content will be transferred to transmit video streams from different places along the route,etc. Technologies developed within 5G-Enhance project will help to facilitate delivery of suchhigh-data-rate user content using 5G eMBB features.Specifics of this scenario are that uplink data rate to support high quality video stream is veryhigh. It is very difficult or not efficient to provide support for such type of users via public 5Gnetwork, especially if there are many other users in the same cell cell (e.g. the spectators ofthe race).To implement such scenario in a more efficient way, the following approach is proposed,considered more suitable for such deployments.Several points within the bicycle race route are selected, where the most spectators areexpected to be concentrated. In these areas public 5G capacity may not be enough to supportboth spectators and high-quality video cameras. In these points, micro operator cells aredeployed to provide additional capacity to be used for uplink video streams.Also, to ensure smooth video quality, seamless multi-link switching, and aggregation isimplemented in the uplink based on MP-TCP including both public operators and microoperators through this being able to use efficiently the available capacity across multipleaccesses.Additionally, a mobile micro operator is foreseen to move along the bicycle race route followinga group of participants as current TV transmission vans are doing. Such mobile micro operatorfollows one or several HD video cameras through this providing direct connectivity withoutrequiring handover. The mobile micro-operator will gather the content from the video camerasand will forward it efficiently to the infrastructure.We also consider the case where other micro operators are operating within the bicycle racearea, so there is a need to share same spectrum with those micro operators for an efficientspectrum usage while being able to satisfy the communication requirements of all theapplications.
The goal of the trial is to demonstrate how technologies developed in WP4 of the 5G-Enhanceproject contribute to improve user experience in eMBB scenario in outdoor environment withhigh density of users.Two stages of Trial 2 are planned:· Pre-trial in Matsuyama (Nov 2019).· Trial 2 in Shimanami (Oct 2020).
The following WPs will contribute to Trial 2:· WP4/T4.1: 5G-Enhance ASNRM: Network sharing architecture· WP4/T4.2: 5G-Enhance ASNRM: Spectrum measurement and learning· WP4/T4.3: 5G-Enhance ASNRM: Spectrum resource management based on database· WP4/T4.4: 5G-Enhance ASNRM: Link aggregation
3. 5G-Enahace Technical Requirement
5G will enable a fully mobile and connected society. 5G-Enhance aims to take this goal to the next step by having an improved seamless connection between mobile devices and services provided for them. In other words, 5G-Enhance addresses the human-centric use cases in the eMBB scenario by having two trials. For Trial 1 (live surgery), users are expected to be able to participate in an interactive class for medical students where video and sensors data will be streamed to them.
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For Trial 2 (sport ad-hoc), it is expected to have HD streaming throughout the race course.Cameras will be installed on bicycles for HD stream throughout the race course. Hence, theessential goal for 5G-Enahce project is to improve the user experience when accessingmultimedia content, services and data and focuses mainly on services with high bandwidthrequirements.To achieve these performance requirements, several technologies have been proposed toimprove 5G-Enhance system performance. The detail will be discussed in detail in Section (4)to improve 5G-Enhance system performance. These technologies include multi-connectivity,and virtual-RAN for Trial 1 and spectrum sharing, micro-operator, link-aggregation, for Trial 2.In order to achieve the required system performance, several issues are needed to be takenoff. The technical requirements will be split into requirements for Trial 1 and Trial 2 which isfurther split into network and spectrum sharing requirements.
3.1 Technical requirements for trial 1
In order to achieve the expected performance in Trial 1, several technical requirements are essential to be realized in the system, including:
• The 5G-Enhance shall support micro-operator networks. These micro-operator networks shall provide coverage in predefined areas (class rooms) with dense users.
• It is inevitable that streaming services will have an asymmetric uplink/downlink traffic rate. Hence, 5G-Enhance shall have the capability to support these users’ requirements for a high dense area scenario. Also, 5G-Enhance shall have the capability of supporting dynamic uplink/downlink traffic that may evolve over a period of time.
• The 5G-Enhance system shall support the utilization of a suitable API for HD camerasand 360 cameras streaming integrated into broadcast/multicast system.
• MC technique with a suitable API in order to allow high transmission throughput and/or increased link reliability.
• The 5G-Enhance users shall support the connection to multiple base stations simultaneously.
• The 5G-Enhance system shall support the use of broadcast/multicast in order to increase both number of users and the utilized bandwidth efficiency in comparison with unicast technique.
• The 5G-Enhance system shall support smart network management in denseenvironment through the utilization of vRAN clusters and suitable API.
• The 5G-Enhance system shall support advanced rf resource allocation in denseenvironment through the utilization of vRAN clusters and suitable API.
• The 5G-Enhance system shall support high spectral efficiency by dynamicallymanaging inter-cell interferences by using vRAN clusters and suitable API.
• The 5G-Enhance system shall support MEC to provide sufficient amount ofcomputational power for increased number of sites and users.
• The 5G-Enhance network components will be integrated with 5GTN platform which isoperated by CWC, UOULU and VTT.
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3.2 Technical requirements for trial 2
Several technical requirements for Trial 2, namely network- and spectrum sharing requirements, which are explained here into two subsections.
3.2.1Trial 2 Network Sharing RequirementsThe following technical requirements are essential to enable networks sharing.
• The 5G-Enhance shall support micro-operator networks that are linked to the internet through either microwave or optical fiber link.
• The 5G-Enhance micro-operator networks shall provide coverage within a pre-defined specific geographical area (race course).
• To enable users to connect to the micro operator network, the 5G system shall support unique network identifiers for micro-operator networks. As well as mechanisms for a UE to identify a micro-operator network.
• 5G-Enhance system shall support a mechanism to enable UE to select which micro operator network to access. As well as a mechanism to detect the availability of a micro operator before attempting to access a cell of this network.
• 5G- Enhance system shall utilize a suitable API to provide the connectivity status and geographic position of all UEs and their radio access points to an authorized user.
• The 5G-Enhance system shall support micro-operator networks as tenant-centric network slices with traffic, QoS, and service separation between tenants, e.g., communication services of one tenant do not interfere with communication services from another tenant.
• The 5G-Enhance system shall support micro-operators network deployed in either licensed or unlicensed bands.
• Subject to an agreement between the operators/service providers, operator policies and the regional or national regulatory requirements, the 5G-Enhance system shall support mobility/hand-over between a micro operator and a public PLMN.
• The 5G-Enhance network shall be able to utilize a suitable API to provide the information regarding the geographic location of coverage area (e.g. radio cell sector coverage) to an authorized 3rd party.
• The 5G-Enhance system shall be able to utilize a suitable API to provide the information about the allocated and free network service resources in the network to an authorized user.
• The 5G-Enhance system shall be able to utilize a suitable API for monitoring the resource utilization in a micro-operator network (radio access point and the transport network (front, backhaul) by an authorized 3rd party.
• The 5G-Enhance system shall be able to utilize a suitable API to provide the information regarding spectrum usage and spectrum usage prediction from the spectrum manager.
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• The 5G-Enhance system shall be able to utilize a suitable API for an authorized 3rd party application to negotiate communication service requirements.
3.2.2Trial 2 Spectrum Sharing RequirementsThe following technical requirements are essential to enable spectrum sharing.
• To realize spectrum sharing, the 5G-Enhance system shall support access to both licensed to unlicensed spectrum bands. The supported frequency bands for spectrum sharing among the micro-operator networks will be both sub 6GHz band and mm-wave spectrum band.
• The 5G-Enhance system shall have the capability of supporting dynamic spectrum allocation between sharing micro operators based on user demands, spectrum prediction and spectrum map over a period of time.
• To answer for the problem of spectrum scarcity, 5G-Enhance systems shall allow reuse of the sharing spectrum in dense areas, to improve spectrum utilization and hence having an improved services.
3.3 eMBB in 5G
For the convenience of a document reader this section copied from D3.1 gives a quickintroduction of 5G use case and some key metrics characterizing user expectations.5G will enable a fully mobile and connected society. To do so, 5G will cover a broad range ofuse cases, which lay within the spectrum of mMTC, eMBB and URLLC [NGMN_2015].According to [Mediatek_2018], the initial phase of 5G deployments lays at the eMBB-URLLCside of the triangle closer to eMBB, see Figure 1. eMBB addresses the human-centric usecases [Lechuga_2018]. It aims to improve consumer experience when accessing multimediacontent, services and data and focuses mainly on services with high bandwidthrequirements.
Figure 1. ITU IMT2020 use cases and initial 5G deployment position [Mediatek_2018].
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Within the families of broadband access, the use cases have been classified in differentcategories by NGMN as early as 2015, as shown in Figure 2 [NGMN_2015].
Figure 2. 5G use case categories definition for broadband access [NGMN_2015].
3.4 Mapping among technologies, trials and use casesFor the convenience of a document reader this section copied from D2.1. This section presentshow technology development and trials in 5G-Enhance map into use cases. There arenumerous studies regarding potential use cases as they reviewed in the previous section. Twouse case families (Broadband access in dense area and broadband access everywhere) arethe most relevant ones from potential use cases described by the NGMN white paper[NGMN_2015].The first use case family (Broadband access in dense areas) is in-line with the indoor trial(Remote surgery) of 5G-Enhance and captures the growing demand of high data rate servicesin urban and crowded area. Many people in small and dense areas create heavy traffic. Inhospital environment, a reliable and consistent service in small and dense areas is required.The first focus is broadband access in the critical venues use case. This use cases means thatmany users are temporarily located in crowded venues. Cell capacity, throughput, linkreliability, spectral efficiency, energy efficiency, etc. in uplink and downlink are target KPIs.Among them, throughput and capacity are significantly important. Many research challengesare associated with this use case family. In 5G-Enhance projects, flexible TDD, multi-connectivity and spectrum sharing technologies are developed and the system performancewill be improved.The second use case family (Broadband access everywhere) is in-line with the outdoor trial(Ad-hoc outdoor sport event) of 5G-Enhance. 5G-Enhance outdoor trial will be supported by abroadband access service during the cycling event in Ehime, Japan 5G-EnhanceThis use caseincludes many research challenges: Coverage problem, undesired data stream interruptionsand others. Thus, it is important to achieve consistency and provide all users with enoughperformance. The target KPIs are same as the first use case family. However, this use casedoes not represent any extremes but a minimum guaranteed service. In 5G-Enhance projects,spectrum measurement and learning, spectrum resource database and management andnetwork sharing and management are developed and the target KPIs will be achieved. Figure3 shows the main characteristics for the trials. In [EU-Commission_2013], the high level KPIsof the 5G PPP are described. 5G-Enhance will contribute to those high level KPIs. Table 1highlights the 5G PPP KPIs.
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Figure 3. 5G-Enhance trials main characteristics.Table 2 shows how the 5G-Enhance research works and how the main used technologiesalign in the trials, 5G-Enhance use cases, system improvement in the form of KPI and usecase families. shows how every technology will assist in improving 5G-Enahnce.While the used technologies in 5G-Enahce project will be explained in detail in Section 4.2 forTrial 1 and Section 4.4.2 for Trial 2. Table 3 provides a high-level summary for the proposedtechnologies which will be incorporated in Trials 1 and 2 and the metrics they aim to enhance.In Table 3, (✔) means improve and (✘) means not related. For instance, multi-connectivitycould be utilized to improve either transmission rate or reliability depending on what informationis being sent over each link (same information or different). vRAN clusters provide a betternetwork and rf resources management by monitoring not only a single eNB but several eNBsand hence providing a significant improvement optimal resource allocation. Spectrummeasurement, prediction and mapping improves the spectral efficiency of the rf spectrum. Thisis done by offloading the extra spectrum from micro operator to another. MPTCP allocates thetransmission into multiple parallel streams hence increasing transmission throughput.
Providing 1000 timeshigher wireless areacapacity and more variedservice capabilitiescompared to 2010.
High 5G-Enhance contributes to higher wirelesscapacity as follows: (1) Developing link andnetwork level techniques to improve the wirelesscapacity (2) Managing the radio and networkresource more efficiently.
Facilitating very densedeployments of wirelesscommunication links toconnect over 7 trillionwireless devices servingover 7 billion people.
Medium 5G-Enhance contributes to high connectiondensity in different approaches as follows: (1)Managing spectrum more efficiently and usingoperated bandwidth. (2) Reducing the requiredbandwidth for a given user data rate by flexibleTDD. (3) Operating networks by efficient radio andnetwork resource use.
Creating a secure,reliable and dependableInternet with a “zeroperceived” downtime forservices provision.
Medium 5G-Enhance achieves secure and reliableconnection by multi-connectivity.
This section describes the system architecture for the trials. The description will include themain network/system elements and functionality for both trials. Moreover, 5G-Enhancenetwork requires the development of several key techniques to enable the required flexibilityand scalability. The new technologies and concepts which will be incorporated in thedemonstrations are briefly described with the advantages they provide for 5G-Enhance Trials.
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4.1 5GTN network architecture
Trial 1 utilizes 5G test network (5GTN), which is the world’s widest 5G test network with openaccess for testing. The network is operated and maintained together by CWC, UOULU andVTT. 5GTN is available primary in the campus area of UOULU, but it could be extended intoother sites. Some special requirements like national radio frequency specifications areidentified, but more detailed analyse and plan should be done during the project.
5GTN is complete 5G test system from infrastructure to applications and services. It allowsunique testing possibilities from prototype devices to complete solutions in a controlledenvironment. The 5GTN network consists of several sites and is well-connected with nationaland worldwide test environments. The 5G Test Network features support the use of 5Gdevices, several frequency bands, orchestration functionalities, and system testing tools. Inthe trial, we have newest test devices with in-depth analytics for a maximal trial experienceand outcomes. Figure 4 below shows the high-level network architecture of 5GTN.
The network includes the following main components:· Communications infrastructure from LTE evolution to 5G radio access. WiFi and IoT
networks, e.g., LoRa integrated· MEC to bring services and applications close to users access· eMBMS for delivering the live video content efficiently to large group of users
simultaneously in LTE/5G· Core network in cloud environment. Virtualized EPC of 5GTN· Cloud systems for applications. Backend servers - serve as data storages, data
processing and video converters· Secure connection to other test sites in Finland and worldwide
Figure 4 .5GTN network architecture.
Trial 1 network configurationTrial 1 considers the 5G network application under very high data rate, indoor (limited mobility),and many users. The trial 1 focuses on the network sharing/management and the application
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of link aggregation and multi-connectivity solutions in the transport and network layers toincrease the data rate.
In Trial 1, we use 5GTN as the main network infrastructure to provide the end-to-endconnection between the hospital operating room and class room. The network configuration ofTrial 1 is shown in Figure 5.
Figure 5. Trial 1 network.
Below we briefly describe this end-to-end network configuration of Trial 1.· Multiple sensors, smart glasses and video cameras are placed in the operation room
to capture various data relate to the ongoing surgery (e.g., 360-degree video, varioussensor readings on the physiology of the patient being operated, etc.). These sensorsand cameras are connected to the Server-PC via router.
· The router will have a connection to the 5GTN network, which is connected to the endusers (medical students, or consultant). The end users in Trial 1 can be in the samehospital building or located remotely.
· In Trial 1, the target is to use a locally deployed 5G network (micro-operator) to stream360-degree video augmented with various sensor reading form the operating room tothe students in the class room. For this, we utilize 5GTN of UOULU-VTT, and virtualRAN platform developed by Accelleran.
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· Multicast/broadcast feature utilizing eMBMS is located in 5GTN at VTT premises andis connected to real cloud management EPC core. Currently eMBMS uses 2.6 GHzFDD eNBs and MME inside VTT core. Alternatively, eMBMS can also use UOULU corewhich allows possibilities for several co-demonstrations. The input data for the eMBMSwill be video stream from the hospital area outputted simultaneously to multiplestudents in the class room via eMBMS.
· 5G-Enhance RAN will provide a platform for multi-connectivity developed in line with3GPP R16 studies for ATSSS. This is illustrated in Figure 6 below.
Figure 6. Multi-connectivity architecture.
The multi-technology vRAN platform supports radio access based on LTE Advanced,5GNR and IEEE technologies. Radio resource management in the RAN is manageddynamically by the RNC which is multi-connectivity and multi-technology aware. Thisframework allows the real-world implementation and trialling of algorithms, for example,cell association, mobility management and link reliability management specified by theWP3 work on multi-connectivity.
The user terminal is capable of supporting multiple simultaneous radio connections(either as part of advanced technology in the R16 device or through additional softwaresupporting multiple RF modem terminations).
Traffic steering is managed by the user plane multipath protocol layer, which is presentboth in the end user device and in the core network gateway. For the purposes of the5G Enhance project two implementations of the multipath layer will be investigated –one based on Multipath TCP, the other based on Multipath QUIC.
A key function of the multipath layer is to decide how to distribute the arriving traffic foreach use over the multiple connections available. 5G-Enhance will investigate thebenefits of assistance data from the RAN controller to help to optimise the multipathdistribution decision problem.
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4.2 Trial 1 Main Technologies
The Trial 1 focuses on the flexible and scalable network design, and the application of linkaggregation and multi-connectivity solutions in the transport and network layers to increasethe data rate. The following technologies will be in focus and adopted/developed within the5G-Enhance project to be incorporated into Trial 1 demonstration:
1. 5GTN:5GTN is a 5G technology and service development platform including a continuouslyevolving RAN and a cloud-based EPC. 5GTN is operated together by CWC, UOULUand VTT. The RAN part contains both 4G-based commercial technologies for usecases requiring multiple users, as well as beyond-4G/pre-5G technologies for morelimited scale use cases. The EPC part is fully virtualized, supporting distribution ofnetwork functionalities both in control plane and user plane. The architecture has alsoan integrated testing and network management frameworks implemented, enablingnew functionalities in these domains to be built on top of the existing building blocks oras parallel implementations complementing the existing functionality.
2. vRAN clusters:Network sharing is related to the evolution of the traditional RAN (4G LTE integratedeNB) towards a disaggregated and virtualised 5G edge and access network.Virtualisation of the RAN brings with its opportunities for architectural innovation. Inparticular, the introduction of cell cluster resource management capabilities into thenetwork. This approach allows for a smarter, more optimal, approach to radio resourcemanagement in dense environments than the classical isolated, black box eNB.Admission control, mobility decisions, interference management can all be managedmuch more effectively by a network function with a more global view of the networkthan just one cell or cell site. Measurement data from each cell and connected UE isshared to a distributed dataset, which enables rapid integration of alternative oradditional features requiring deep real-time knowledge of network conditions.
This open and disaggregated approach to RAN architecture allows for the integratedmanagement of multiple technologies in a common framework. The high-levelarchitecture for a virtualized RAN cluster is shown in Figure 7.
3. Multi-connectivity techniques:MC is defined as the capability of a UE to connect to multiple APs simultaneously. Itprovides several benefits for 5G-Enhance networks including:
· higher data-rates, as MC is a form of data aggregation, hence additionalresources can be used for data transmission.
· higher reliability through data duplication and/or inter-frequency transmissions· seamless connectivity by reducing the handoff latency and the overall delay.· reduced jitter with data duplication by minimizing the variance in latency
[Aijaz_2018].· higher energy efficiency by using micro DTX [Ternon_2014].
The multi-connectivity techniques will be adopted in the Trial using Accelleran vRANcluster controller platform; for example, as illustrated in Figure 8.
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Figure 7. Illustration of a virtualized RAN.
Figure 8. Illustration of multi-connectivity by using Accelleran vRAN cluster controllerplatform.
4. Multicast feature:In the Trial multiple stream captured by 2D and 3D cameras are optionally streamed tothe end user devices using multicast feature, which can be accomplished either byusing standard multicasting in IP networks or eMBMS within mobile networks (LTE).Currently, there is also active standardization ongoing towards enabling emBMS in 5G.eMBMS is the best alternative for accomplishing this since it is operational in 5GTN.
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The technologies implementing multicast/broadcast streaming in mobile networks canoptimize bandwidth usage and improve the spectral efficiency as well as throughputand are therefore extremely important in eMBB scenarios that focus on delivering thecontent on high throughput. For such scenarios as in our Trial 1, multicasting the samestream to multiple users in class room is extremely beneficial for decreasing thenetwork load and waste of resources.
The main components for eMBMS usage include eMBMS server, eMBMS supportedEPC and eNBs as well as end devices with LTE broadcast middleware and playerapplication. Currently we are using Samsung and Bittium end devices.
4.3 Open issues for Trial 1
There are few open issues for trial 1 network architecture, although the network is alreadyoperational. The main concerns are number of end users, it is uncertain how many studentsor specialist use the service in practise, some concerns for availability of user end devices, 5Gdevices e.g. smart phones and modems, and capability to install trial 1 system in otherresearch partner sites.
Multicast option in trial 1 can be affected by lacking the support of eMBMS supporting 360/VRvideo end device applications that can both receive the multicast stream via 5G mobile networkas well as playback the stream via 360 application. Also, global integration when performingtrials outside of Finland can be difficult.
4.4 Trial 2
4.4.1 System architecture
As was mentioned in the outline (Section 2), Trial 2 is focused on eMBB scenario in outdoorenvironment with high density of users mixed with several users requiring high data rate in theuplink.Such scenario will be available during Ehime bicycle race, where there will be a large numberof participants and spectators to create dense user environment. In addition, one of the projectpartners (Ehime CATV) will be doing commercial TV translation of the bicycle race usingmultiple high-definition cameras distributed within the race route and mounted on theparticipant bicycles.During the event, within the race route there will be areas with high concentration of spectators(e.g., start, finish, mountain part with nice view) and areas with almost no spectators (e.g.,straight roads or bridges).While in the areas with low concentration of users it could be possible to provide requiredquality of service for uplink video stream using only public networks, in the areas with highconcentration of users capacity may be not enough. Deploying micro operator in the areaswith high density of users for the purpose of supporting uplink video stream would significantlyimprove video quality, number of simultaneously supported uplink video streams, and alsooffload public 5G networks for the benefit of spectators.Also, it is planned that at least one micro operator would be deployed inside a car and willfollow one or several users equipped with high-data-rate cameras. Such mobile micro operatorwill exclusively serve these users. It will use micro operators and public operators for backhaul.In addition to deploying micro operators, another measure is typically used to improve uplinkvideo stream quality – multiple links using several radio interfaces. There is a specialequipment between camera and transmitters that splits an uplink stream from camera intoseveral streams and distribute them to several radio interfaces. On the server side these
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streams are merged back into one stream. Trial 2 also uses this multi-link technology basedon MP-TCP.HD cameras mounted on race participant bicycles are moving along the race route. Whilemoving, they experience different areas:• Areas with only public operator service• Areas with both public operator service and micro operator service.
There is a need to adaptively switch multiple links from one camera among these public 5Goperators and micro operators. To assist in this adaptive multi-link management, a specialsystem is deployed. It contains radio environment map that helps to select location and timeto switch links between different base stations (public and non-public) and to adaptivelydistribute video traffic between active links. This system helps to reduce overhead associatedwith switching radio interfaces between different cells, frequencies, and networks.Micro operators use specific frequency band. Public operators or other radio systems do notoperate in this band. However, within this band, different micro operators could share the samefrequency.To emulate such situation during Trial 2 several co-located micro operators are deployed,where one micro operator serves high-definition video camera users, while other operatorserves different type service, such as shopping mall (uO Y in Figure 9). These co-located microoperators share the same frequency band. For the spectrum usage prediction, spectrummeasurement and spectrum usage modelling are necessary.Trial 2 system architecture is shown in Figure 9. It includes the following key elementshighlighted in the text above:• Users with high definition cameras supporting several radio interfaces
o Including terminal side multi-link support software• Public 5G networks• Micro operators• Radio environment map database
o Connected to multi-link manager• Spectrum usage prediction database
o Connected to spectrum sharing manager.
Figure 9. Trial 2 system architecture.
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4.4.2Main technologies
Different technologies developed within WP 4 contribute to Trial 2. Brief description is asfollows.T4.1: Network sharing architecture:• Micro operator – micro operator eNB and CN are developed and will be used in Trial 2.• Mobile micro operator – at least one micro operator eNB will be installed on a car and will
follow one or several high-definition cameras during the race together with a self-backhauled edge node which enables the content pre-processing before using the side ofthe road infrastructure.
• Adaptive reconfigurability for spectrum sharing – micro operator could adaptively changecentral frequency and bandwidth.
• Millimeter band technology – some of micro operators could operate around 30 GHz.
T4.2: Spectrum measurement and learning:• Spectrum measurement – using portable spectrum analyzers, spatial-temporal spectrum
usage measurement is performed• Spectrum usage modeling and prediction – based on the results on spectrum usage
measurement, spatial-temporal spectrum usage model is created using learningalgorithms
• Spectrum sharing support – based on the spectrum usage model,policies/recommendations for spectrum sharing are provided to co-located microoperators.
T4.3: Spectrum resource management based on database:• Spectrum measurement – using special software on smartphones, signal strength from
different PLMN operators and micro operators is measured and reported to a database• Radio environment map database – based on the signal strength and location information,
radio environment database is created• Multi-link transmission support – based on the UE location information, radio environment
database could send recommendations when to switch links between different cells.
T4.4: Link aggregation:• Multi-link connectivity based on MP-TCP – based on MP-TCP multi-link transmission is
implemented for high-data-rate uplink video stream upload• Multi-link cluster handover – joint handover decisions for a cluster of co-located cells• Multi-link traffic switching and splitting management – management of high-data-rate
uplink traffic switching and splitting among multiple links with PLMN operators and microoperators.
Figure 10 summarizes how WP 4 R&D contributes to Trial 2. They are described below in moredetails.
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Figure 10. Trial 2 contributing technologies.
4.4.2.1 Micro operator
Micro operator for Trial 2 uses LTE eNodeB and 4G CN as a basis.Two new features are implemented on top of 4G eNodeB:• Support of mmWave frequency band• Support of fast adaptive reconfiguration of central frequency and bandwidth.
One new feature implemented on top of 4G eNB support of the millimeter wave frequencyband. Central frequency is around 28 GHz and bandwidth in around 20 MHz. In addition toseveral such eNBs, there are several devices available that could communicate with sucheNBs. This will allow to consider both regular and microwave frequency bands currentlyconsidered for 5G and Beyond 5G systems in dense environments.Another feature implemented on top of 4G eNB is support of the fast adaptive reconfigurationof central frequency and bandwidth for spectrum sharing. Central frequency is around 2.6GHz. Bandwidth is 5MHz or 10MHz.Fast real-time spectrum sharing would require specific PHY and MAC design of eNB andterminals and thus is not supported in Trail 2. However, in case of long-term predictablespectrum usage variation (for example, within one day or one week) micro operator couldreconfigure fast enough to do adaptive spectrum sharing. This case is considered in Trial 2.Four new features are implemented on top of 4G CN:• Interface with spectrum usage prediction database• Spectrum sharing manager• Interface with radio environment map database• Multi link manager.
Spectrum Usage Prediction Database collects spectrum usage measurements fromspectrum analyzers for several co-located micro operators, creates spectrum usage model foreach of such operator and assist these micro operators in adaptive spectrum sharing.
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Micro operator CN has an interface with the spectrum usage prediction database. Thisinterface is used to receive spectrum sharing policies/recommendations from the database.The function inside a micro operator CN that implements such interface is called SpectrumSharing Manager. In Figure 9 only one instance of such function is shown, serving three microoperators. How many such functions are used depends on deployment scenario: one per eachmicro operator or one per several micro operators.Spectrum Sharing Manager analyzes current configuration (central frequency and bandwidth),traffic load, number of users etc. received from each of the micro operators, as well asspectrum sharing policies/recommendations received from the database. Based on thisinformation, Spectrum Sharing Manager could make decisions to reconfigure one or severalco-located micro operators sharing the same frequency band.
Radio Environment Map Database collects signal strength of PLMN operators and microoperators and creates radio environment map. This map shows coverage from differentoperators along the route of the bicycle race. Based on this map and device locations, radioenvironment map database provides recommendations to multi-link transmission managementfunction when to switch links between the operators.Micro operator CN has an interface with the radio environment map database. This interfaceis used to receive recommendations when to switch links between operators from thedatabase. The function inside a micro operator CN that implements such interface is calledMulti Link Manager. In Figure 9 only one instance of such function is shown. How many suchfunctions are used depends on deployment scenario.Multi Link Manager analyses number of multi-link users, their QoS requirements, locations,multi-link configuration, available operators, their available capacity, recommendations fromradio environment map database. Based on this information, Multi Link Manager makesdecisions to adaptively reconfigure multi-link connections. Multi-link connections areimplemented using MP-TCP.
Mobile micro operator is a micro operator equipment installed on a car that can follow specificparticipants of a race. Mobile micro operator uses LTE eNB and an adapted 5G CN. It uses3.5 GHz or 3.7 GHz and bandwidth up to 20 MHz. It cannot use directional antenna forbackhauling e because of the movement. Instead, it will use other micro operators and publicoperators to connect to the Internet.
4.4.2.2 Spectrum Usage Prediction
Several spectrum measurement systems will be used, where each one consists of severalportable real-time spectrum analyzers and/or SDR sensors with device control PC, systemmanager, local data server and local storage. Figures 11 and 12 show the spectrummeasurement system and signal processing for spectrum measurement in each device controlPC, respectively. The system manager can control the device parameters includingmeasurement time and period and measurement center frequency and frequency bandwidth.The proposed system will focus on measuring the RSSI value obtained by FFT-based powerspectrum estimation. The bandwidth is between 20 and 40 MHz depending on themeasurement device. Then, the spectrum usage detection by energy detection and signal areaestimation are performed to acquire the spectrum usage in the measurement area. Thedetection mask size setting and noise floor estimation are utilized to improve the accuracy ofthe spectrum usage detection. The data server is responsible for the fusion process of all theobserved data by devices and duty cycle estimation.
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Figure 11. Spectrum measurement system.
Figure 12. Signal processing for spectrum measurement.
Learning algorithms for spectrum usage modelling and prediction are focused on two topics:the model of spectrum usage in the time domain and prediction of spectrum usage ratio (duty-cycle). For the spectrum modelling part, a flexible and scalable spectrum usage model in thetime dimension is proposed based on mixture distribution in which more than one distributionis employed. The accuracy obtained by mixture distribution can be further improved by settingthe number of distributions and their parameters appropriately. For this, we employ anonparametric Bayesian model.For the prediction part, two approaches are being investigated. The first approach is based onautoregressive moving based prediction of the duty-cycle. The second approach is based onmachine learning. Multiple deep learning algorithms such as Convolutional Neural Networksand Long Short-Term Memory are being investigated to accurately estimate the duty-cycle.Based on the obtained results the total available spectrum can be adaptively allocated betweenserving micro operators seamlessly. Hence, maximizes the spectral efficiency and provides animproved QoS for users.
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4.4.2.3 Radio Environment Map
A software is developed on top of android operating system that periodically collects RSRPmeasurement and send it to database together with location information. Several mobile nodeswill be incorporated for measurements such as smart phones, vehicles and wireless LANterminals. Radio environment map is created in the database. For each of the measured pointsthis radio environment map includes the following information:• Location of mobile sensor• PLMN ID• Cell ID• Frequency Band• RSRP (signal strength), RSRQ, RSSI, SNR, CQI• Time of measurement
The gathered information is thoroughly analyzed on the database and used to improve thereliability, spectrum sharing and area design for the proposed system. In this task, thespectrum resource management for 5G systems is discussed for improving the spectrumefficiency and satisfying the demand of users. Also, it is expected that radio environment mapdatabase will assist MP-TCP algorithm for adaptive multi-link transmission.The basic structure of spectrum resource management system with spectrum database isshown in Figure 13.
Figure 13. System structure of spectrum resource management based on spectrumdatabase.
5.Trials hardware setup and trial procedureThe trials hardware design and setup have been carefully investigated taking into accountseveral aspects including human personal, available budget and equipment while ensuringthat the scale of trials will provide a valid proof of concept on the possible enhancement for thefuture 5G systems which we believe will have a significant impact on currently deployed 5Gnetworks through the utilization of proposed algorithms and techniques in 5G-Enhance project.In this section the hardware setup and procedure for both trials will be described.
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5.1 Trial 1 setup and evaluation scenarios5.1.1 System configurationFigures 14 (a) and (b) illustrates the general configuration for Trial 1. The extent to whichresearch results, algorithms or techniques can be implemented into a deployable networksolution (and Trial 1 deployment) will be established during the project.The main components of Figure 14 (a) and (b) are:
· Server-PC: A server PC, where data (including video, audio, sensor data) generatedin the operating room is stored and processed. Operating room components (e.g.,smart glasses, 360 video camera, sensors) and end user devices of the class room(e.g., VR glasses, tablets, smart-phones) are connected to the Server-PC via a router(LTE/5G or Wi-Fi).
· 360 video camera (Ricoh Theta V): It is a 360-degree camera and records overallvideo of the operating room. Multiple streams capture by the camera (for 360 view) isstitched and processed to get a single data stream, which is transferred to the Server-PC.
· Sensors: Various sensors elements will be deployed to monitor the physiology of thepatient being operated. In the demo, Shimmer3 GSR is used to monitor heartbeats.Other sensor elements will be considered during the project.
· Smart glasses (Vuzix M300): It is a headset, that can be used by a doctor or nurse inthe operating room. Vuzix can capture video/audio and transfer to Server-PC. Vuzixalso has a small display, where doctor/nurse can see sensor data c. Thus, Vuzix M300headset has dual purpose in the demo; either to assist doctor/nurse with sensor data,or to feed the audio/video (doctor/nurse view) of the operating room to the end users.
Figure 14 (a) Trial 1 hardware architecture in Operating Theatre.
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Figure 15 (b) Trial 1 hardware architecture at Student Theatre.
· End user devices: It can be VR glasses, tables, or smart-phones with or withouteMBMS support. End devices get connected to the Server-PC via 5GTN core androuter or multicast routing. End users will have opportunity to view video captured by360 video camera and smart glasses (doctor’s view), audio, and sensors data.
· Small Cells: The RAN platform will support a range of small cell options including LTE,multicarrier LTE Advanced and 5GNR as well as the potential to include WiFi basedAPs.
· Virtual RAN Server Platform: The RAN control functions will be hosted on an off-theshelf small form factor server supporting 10GB ethernet networking interfaces. vRANsoftware will be managed via open standard network orchestration (Kubernetes) andprovide tools for remote management and monitoring of the network and user activity.
5.1.2 Evaluation procedureThe preparation of Trial 1 will be carried out step by step as follows:
· Step 1: First, UOULU will test the 5GTN to make sure that the core-network is fullyfunctional and available to all partners to deploy the algorithms/techniques developedin the project.
· Step 2: By using the basic hardware available in UOULU, pre-trial will be organized byUOULU and report the status of the network to all involved partners. Initial setup willbe based on LTE and WiFi connections. Then UOULU, will work toward obtaining andintegrating the 5G capable devices.
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· Step 3: Accelleran vRAN cluster platform will be integrated with 5G Core.Interoperability with end user devices will be tested and proven. MC testing will beperformed to demonstrate performance improvement vs Single Connectivity.
· Step 4: Test procedure carried out in Step 1 to Step 3 uses single cast transmissiontechniques to stream live video to the end user devices. In order to optimally utilizebandwidth and improve spectral efficiency, VTT will deploy multicast transmissiontechniques via eMBMS.
· Step 5: Finally, the complete trial 1 setup will be tested by integrating 5G capabledevices.
5.1.3 Expected resultsIn the prototype of demo in 2018, each hardware component (camera and sensor) wereconnected using existing technologies; 4G (LTE), Wi-Fi and Bluetooth radios and PC levelcomputing power for video and data analysis and processing. Also singlecast is used fordelivering the streams to users. The data rate was around 10s Mb/s, which was offed justacceptable quality of service with rather long latencies, uncontrolled connection and servicebreaks and low-resolution videos.
During Trial 1 in 2020, it is expected that 5G devices and modems are available. New HD and360 cameras, new sensors and next generation end user devices will be used. Requiredtransmission data rate and need for data processing (video, audio and data processing andanalysing) will increase. Several HD cameras will be used, where they are used in the sameroom at the same time. Also, number of sites and viewers in remote education and remoteconsultancy trial cases will be bigger than in the first phase. Requirements for network andcomputing will be more demanding.
Compared to situation 2018, the following improvement are planned for 2020 (trail 1):
· Data and video stream data rate increased >100s Mb/s – local 5G and high capacityinternet connections needed.
· Support larger number of end users (around 10 users in demo, however the developedsystem is scalable) and several multi-remote connections.
· Quality of service will meet expectations of end users, for example HD video is in useand major end user device problems i.e. over-heating of smart glasses solved orunderstood.
· Efficient use of bandwidth through the utilization of broadcast/multicast technologies.For instance, 10 simultaneous users require 10x10Mbit/s = 100Mbit/s total networkcapacity only for video streaming in unicast way. While when using broadcast/multicastonly single 10 Mbit/s is needed for delivering the same content to all users. Henceincreasing number of multicast users compared to singlecast. Also, decreasing thespectrum usage and network bandwidth compared to singlecast.
· High achievable data rates through using MC techniques. For instance, a userconnected to single AP can obtain 10Mbit/s. While when utilizing MC the same usercan connect to several APs (N) and the results data rate is Nx10Mbit/s.
· Multiconnectivity will provide much improved flexibility to tune QOS profiles to deliverhigh-throughput on the one hand or high-reliability delivery on the other. Dynamicintelligent management of the virtualised RAN network resources supports innovative
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schemes for multiconnection management to significantly improve the userexperience at cell edge and improve the reliability of handover during mobility.
· Trial 1 will enable remote class room and consultancy. For example, surgery room inOulu Finland, and student class room or consultancy could be Japan.
5.2 Trial 2 evaluation scenarios
5.2.1Spectrum sharing
It is expected that one scenario of spectrum allocation for private operators would be allocationof some band for shared use by several micro operators. This would be different microoperators serving different groups of users, for example, inside factories, within shopping mallor entertainment park, within a service area on a highway.If two or more micro operators are co-located, that is, could cause harmful interference to eachother when operating on the same frequency, there is a need to manage spectrum sharingamong them. This will improve spectrum usage efficiency and QoS support.Within Trial 2 it is planned to evaluate such spectrum sharing scenario.
5.2.1.1 System configuration
System configuration for spectrum sharing evaluation is shown in Figure 15.
Figure 16. System configuration for spectrum sharing.
Two micro operators are co-located, uO XN and uO Y. Micro operator uO Y serves regularusers, for example, highway service area users. Micro operator uO XN serves bicycle raceparticipants that have cameras mounted on their bicycles.Micro operator uO Y that serves regular users is available every day, so it is possible to dospectrum usage measurements in advance and create spectrum usage model. Thesemeasurements and spectrum usage model are stored in spectrum usage prediction database.
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Both micro operators uO XN and uO Y have modified eNBs that allow them to perform adaptivespectrum sharing with a reasonable speed. In other words, they can reconfigure their eNBcentral frequency and bandwidth without long interruption of service.There is a spectrum sharing manager as part of a micro operator CN. In Trial 2 for simplicitythere is only one instance of spectrum sharing manager for two micro operators. Based onmessages from spectrum usage prediction database and measurements from micro-operators, spectrum sharing manager reconfigures central frequencies and bandwidth of microoperators uO XN and uO Y. Example of such reconfiguration is shown in Figure 16.
Figure 17. Example of reconfiguration for adaptive spectrum sharing.
5.2.1.2 Evaluation procedure
Evaluation procedure for the spectrum sharing scenario has two stages:· Measurement and modelling· Adaptive spectrum sharing.
Measurement and modelling stage is as follows:1. Long-term spectrum usage measurements are performed for different locations within
coverage area of micro operator uO Y.2. Measurements are stored in the spectrum usage prediction database.3. Spatial-temporal model of spectrum usage of micro operator uO Y is created.4. The model should show that there are some changes in the spectrum usage of micro
operator uO Y during the day or week of the bicycle race that allow to do beneficialspectrum sharing with micro operator uO XN.
Adaptive spectrum sharing stage is as follows:1. Micro operators uO Y and uO XN are co-located and share the same spectrum by using
different frequency bands (otherwise they will cause harmful interference to each other).2. At some point of time during the period of bicycle race spectrum usage prediction
database predicts that number of users of micro operator uO Y has decreased and thereis a possibility to give more spectrum to micro operator uO XN.
3. Spectrum usage prediction database sends a message to spectrum sharing managercontaining information that micro operator uO Y has decreased its spectrum usage.
4. Spectrum sharing manager sends a message to micro operator uO Y requesting to reportcurrent spectrum usage.
5. If spectrum usage prediction and spectrum usage measurements for micro operator uO Yare similar and show that there is some available spectrum, spectrum sharing manager
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requests central frequency and bandwidth reconfiguration to micro operators uO Y anduO XN.
5.2.1.3 Expected results
· Based on the spectrum usage database and appropriate spectrum predictionalgorithms, the required spectrum at uO Y can be forecasted. Hence, the extrafrequency resources can be offloaded to uO Xn and thus providing the necessaryresources for high data rate users especially when advanced techniques such ascarrier/link aggregation is being used.
· The main targeted metric here is which is defined as the ratiobetween the total allocated spectrum between sharing micro operators to the actuallyused spectrum measured at spectrum sharing micro operators.
=
· The reason for using and not spectral efficiency metric is
because of different modulation types and path losses affect the obtained throughputand we want a more generic metric to identify spectrum sharing. Hence, the
will be utilized.· Another target sub-metric is the prediction error of spectrum usage ratio (i.e., duty
cycle), which is defined as RMSE (Root Mean Square Error) between the duty cyclemeasurement and the predicted duty cycle. Specifically, it is expressed as follows.
( ) =1
( ( ) − ( ))
where N indicates the number of duty cycle measurements, Ψ( ) is the duty cyclemeasurement at time instant t and Ψ( ) is the predicted one. Minimizing ( )leads to accurate estimation for the statistical information (accurate database). Hencehaving an improved spectrum sharing support.
· Current networks do not support spectrum sharing and the spectrum allocation is fixed.This can create a scenario where one area has more spectrum that it actually needswhile a neighbouring cell is overcrowded with users. Based on our proposed algorithms(accurate spectrum detection, spectrum modelling and prediction), we aim to adaptivelyallocate the available bandwidth based on demand requirements between frequencysharing uOs. Hence increasing the metric.
· At this point in the project, defining accurate values for the improvement in and is a difficult task. As spectrum usage and
measurements differ from one area to another. In other words, it is site specific.Nevertheless, the target is to provide enough spectrum resources for streamingcameras when they enter uO Xn coverage area through efficient spectrum allocation.
· Improvement numbers can be obtained after measuring spectrum usage on site(coverage area of uO Y) and comparing the results with the total allocated frequencyto estimate spectrum usage ratio.
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5.2.2Multi-link transmission of high-data-rate uplink video stream
5.2.2.1 System configuration
System configuration for multi-link transmission of high-data-rate uplink video stream is shownin Figure 17.
Figure 18. System configuration for spectrum sharing.
HD cameras generating high-data-rate uplink traffic are mounted on bicycles of several raceparticipants. They move along the race route.HD cameras are connected to a device implementing MP-TCP client software that can splithigh-data-rate stream from the camera into several links. Correspondingly, this device alsohas several UEs, capable of connecting to different public operators and micro operators(having radio interface capability and subscription).Bicycle race route is covered by several public operators. Also, some areas of particularinterest for the race viewers are additionally covered by micro operators.When a user that has high-data-rate uplink stream, MP-TCP client software, and multiple UEsmoves along the route of the race, it has to switch links between eNBs of different operatorsand distribute traffic between the links depending on each link capacity.To assist seamless switching between eNBs of different operators, radio environment mapdatabase is created. Based on predicted location information of users with cameras, radioenvironment map could provide information on available eNBs to connect to.To use such information, multi-link manager function is used in a CN. In Trial 2 for simplicityonly one multi-link manager is deployed. Based on messages from radio environment mapdatabase and measurements from operators and terminals, multi-link manager performsreconfiguration of each uplink multi-link transmission user.One micro operator is mounted on a car. This car follows one or several users with cameras.It uses micro operators and public operators as a backhauling connection and acts as a mobileterminal for the public operators and the other micro-operators deployed at the side of the road.
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5.2.2.2 Evaluation procedure
Evaluation procedure for the multi-link transmission of high-data-rate uplink video stream hastwo stages:· Measurement and creating radio environment map· Adaptive multi-link transmission.
Measurement and creating radio environment map stage is as follows:1. Measurements are performed along the route of the bicycle race2. Each measurement includes several parameters such as
a. Parameters related to frequency band, PLMN ID and cell IDb. Parameters related to signal strengthc. Parameters related to time and location of the measurement.
3. These measurements are collected in the radio environment map database.4. Radio environment map is created based on processing the measurements.
Adaptive multi-link transmission stage is as follows:1. A user with high-definition camera, MP-TCP support and multiple UE support moves along
the route of the bicycle race.2. This user periodically reports its location to multi-link manager, which processes it and
sends predicted future user location information to the radio environment map database.3. Also, multi-link manager sends current multi-link configuration of this user to the radio
environment map database.4. In response, radio environment map database sends to the multi-link manager
recommended link configurations for some of the future locations together with a reason tochange connection (for example, end of coverage area for one of the micro operator eNBswith which there is an active connection).
5. After that and periodically, terminals and public and private operators provide additionalmeasurements to the multi-link manager. Such measurements may include:
a. Measurements related to signal strength for active and potential multi-linkconnections
b. Measurements related to available capacity of the cells of public operators andmicro operators
c. Measurements related to actual throughput and other QoS parameters on each ofthe active links
6. Taking into account all received information, multi-link manager makes decision on multi-link reconfiguration for each of such users. In particular, multi-link manager performsreconfiguration of the following parameters:
a. Number of links usedb. To which eNB each used link is connectedc. Total supported traffic rated. Which part of traffic distributed to each link
7. Micro operator mounted on a car that follows one or several high-data-rate users is alsoviewed as one of the multi-link users (for the purpose of backhauling connection). Themobile micro-operator will be evaluated taking into consideration the backhauling qualityof the video as well as the direct video connectivity quality, practically assessing the self-backhauling capabilities of the proposed infrastructure.
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5.2.2.3 Expected results
During the previous bicycle race in Ehime in 2018, each camera was connected to the multilinkdevice that was connected to four LTE USB cards. Each card was able to provide around 1Mb/s data rate, which was combined to have total of 4 Mb/s data rate.Also there were areas where data rate on all four LTE USB cards decreased considerably forsome period of time, probably due to coverage in the area with a lot of mountains and tunnels.During Trial 2 in 2020, it is expected that HD cameras will be used. Expected data rate percamera is 10-15 Mb/s. Also, it is expected that several cameras will be used, where they couldbe nearby at the same time. Also, there would be stationary cameras, for example, on thebridges or other places with interesting and scenic view.Compared to 2018 race, the following improvement are planned for 2020 (trail 2):· Video stream data rate increased from 4 Mb/s to 10-15 Mb/s per camera.· We try to avoid areas of interest that will not support required data rate (coverage
extension using micro operators and mobile micro operator).· Increase number of cameras that could be used in parallel and in nearby location in order
to support multi-angle interactive view of the race.
An additional benefit of using micro operators would be offloading most part of high-data-rateuplink traffic from public operators.
6.Time plan and partners roles
6.1 Time plan and availability
6.1.1 Trial 1· 28th of March, 2019: project plan ready and use case presentation and query for medical
students (digitalization in medical studies workshop at Oulu university hospital/TestLabwith OuluHealth)
· 29th of March: 5GEnhance partners on-site visit Oulu .· End of April (Week 17): Workshop in Japan .· 12th of June, 2019: 360 video/remote education technical prototype at Pre-HIMMS.· 11th -13th of June, 2019: HIMSS Europe 2019 and Health 2.0 in Helsinki (healthcare
information and management systems society event) .· September 2019, Initial implementation of 4G MC prototype will be demonstrated
(simple algorithms).· December 2019, 4G MC prototype available for testing with v2 algorithms.· By the end of 2019, 360 remote education/consultation technical demo/prototype
available for 5G Enhance, first tests with multicasting.· April 2020, 4G/5G MC HW available for trial.· By the end of 2020, the eMBB enabled 360 remote education/consultation prototype is
ready to be used in Finland and Japan.
6.1.2 Trial 2· April 2019, project partners visited Trial 2 site at Ehime prefecture. Potential points for
micro operator installation have been selected. Several installation points were checkedfor possibility to connect to Internet via mmWave point-to-point connection link.
· May – June 2019, development of evaluation scenarios and metrics for Trial 1.· July 2019 – March 2020, each partner develops their system (micro operator, spectrum
usage prediction database, radio environment map database, mobile micro operator).
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NICT will develop protocols for interfaces between micro operator CN functions and twodatabases.
· November 2019, pre-trial will take place in Ehime, Japan. During the pre-trial, eachpartner can field test their developed system and algorithms.
· April – August 2020, integration of all partners equipment followed by laboratory testsfor the integrated equipment.
· April – September 2020, measurements collection for spectrum usage prediction andradio environment map.
· October 2020, final integration and tests for equipment and technologies. Trial 2 duringbicycle race and HD video streaming from multiple cameras mounted on raceparticipants bicycles to stream different places along the route in Ehime, Japan.
6.2 Measurements to maximize the project impact
To accelerate the adoption and impact of the technologies developed in 5G-Enhance, we haveplanned to implement suitable steps in terms of dissemination to industry, in learnedpublications and conferences and moreover in terms of standardization contributions.
· 5G-Enhance will organize a workshop within IEEE VTC Fall 2019, between 22–25September 2019, in Honolulu, Hawaii, USA. The workshop title is “5G and Beyond*Technologies for Ultra-Dense Environments “
· We are aiming to attend events such as IEEE Globecom, EuCNC2020, or PIMRC werea demonstration and tutorials of latest 5G-Enhance findings/results will be provided topeer researchers.
· Publication of scientific results and of practical experiences to the largest scientificand industrial communities, high profile conferences and journals. Target events/conferences include: IEEE ICC, IEEE PIMRC, IEEE GLOBECOM, IEEE INFOCOMand IEEE WCNC. We will also target top peer-reviewed journals, including, amongstothers, IEEE Transactions on Wireless Communications, IEEE JSAC, and IEEECommunication Magazine. The project targets to have at least 2 publicationssubmitted per year to top journals and 5 per year to conferences.
6.3 Partners roles5G-Enhance network requires the development of several key techniques to enable therequired flexibility and scalability of the network in design/implementation as well as enhancingspectrum resourcemanagement. A brief description of every partner role is provided in this subsection. Tosummarize every partner role, Figure 10 shows the main partners involved in the 5G-Enhanceproject.
6.3.1 Trial 1 partners and rolesThe work is divided between partners as follows for Trial 1:
• UOULU will participate and lead the architecture design and configuration in the Trial1. Oulu will handle the planning and execution of Trial 1. UOULU 5G test network haskey components for the network sharing based on SDN (software defined network) /NFV (network function virtualization). One of the key tasks is the design of merging thekey-components/technologies in order to meet the 5G KPIs requirements for 3D remoteclass for a real-time surgery trial. Oulu main contributions to 5G-Enhance workpackages are to WP1, WP2, WP3, WP4, WP5 and support in WP6.
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• VTT will focus on developing and integrating 5G multicasting algorithms as a part of atestbed for improved throughput and energy efficiency. Algorithms for cell selection ina multi-connectivity scenario will be also developed in conjunction with Trial 1, but livedemonstration for multi-connectivity can be difficult. Also, VTT will participate inestablishing the interconnection between FHG 5G Testbed and 5GTN in order toperform a system-wide evaluation of the trial scene if needed. Moreover, the evaluationand test capabilities for network sharing within 5GTN will be done. VTT maincontributions to 5G-Enhance work packages are to WP1, WP2, WP3, WP5 and WP6/
• Accelleran is experienced in small cell and distributed cloud RAN solutions, hencethey will support Trial 1 by providing small cell and vRAN equipment which supportsthe testing of multipath connectivity, as well as assisting in the vRAN deployment.Accelleran will ensure that the platform has the required multi-connectivity capabilitiesto allow evaluation of the gains such an approach and protocols can offer in a 5G densemulti-operator network. Accelleran will help in the definition of trials within realisticscope of available and project development functionality, products and capabilities aswell as the definition of the multi-connectivity use-cases. Accelleran will ensure thatmaximum benefit to the project can be brought by reusing developments betweenpartners Accelleran and Fraunhofer FOKUS from other R&I projects. Accelleran maincontributions to 5G-Enhance work packages are to WP3 as well as supporting WP2,WP4, WP5 and WP6.
6.3.2 Trial 2 partners and rolesThe work is divided between partners as follows for Trial 2:
• NICT will participate and lead in the eMBB Trial 2 as well as will handle the planningand execution of Trial 2. NICT will develop, 5G test Networks that will be used to deploy,test, validate and demonstrate the concepts of 5G-Enhance in regard to the trial. NICTwill contribute to the definition of procedures to enable the spectrum, network sharingand multi-connectivity aspects of the use of unified cases. NICT will developarchitectures and provide high-level 5G procedures to support network sharing inaddition to contributing to 3GPP standardization. Also, NICT will ensure that thedeveloped technologies are supported by the 5G prototype system. Moreover, NICTwill contribute to database architectures to enable efficient spectrum utilization. NICTwill contribute to the link aggregation by the creation of novel MPTCP schedulers.MPTCP enable connections to distinct systems such as WiFi and LTE concomitantlyand experience higher data rates owing to its capabilities of splitting data throughmultiple TCP subflows. NICT main contributions to 5G-Enhance work packages are toWP1, WP2, WP4 and WP5 as well as supporting WP6.
• TUAT is to develop the spectrum management/sharing system to be used betweenmacro base station and uO concept (uO proposed by the University of Oulu). The goalis to achieve both a reliable spectrum sharing and efficient spectrum allocation betweenmacro operator and uOs through the utilization of smart spectrum concept. TUAT hasdeveloped a comprehensive spectrum measurement system and learning algorithm toprovide proper information to the database. For Trial 1, the enhanced spectrumresource management based on the obtained information for spectrum usage in thetime domain. TUAT will provide spectrum measurements (based on spectrumanalyzers and SDRs) in the time domain to extract channel usage and other usefulstatistics. Also, the development of learning algorithms for spectrum usage modelingand prediction to be used in spectrum sharing paradigm. The proposedideas/techniques will be investigated through both analytical and comprehensive
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demonstration experiments. TUAT main contributions to 5G-Enhance work packagesare to WP2, WP4 and WP5 as well as supporting WP6.
• UEC is to develop the spectrum management / sharing system to be used betweenmacro base station and uO concept (uO proposed by the University of Oulu). The goalis to achieve both a reliable spectrum utilization between macro operator and uO] andefficient spectrum allocation between multiple uOs through the utilization of smartspectrum concept. UEC has developed a comprehensive spectrum measurementsystem. For Trial 2, the enhanced spectrum resource management based on theobtained information (spectrum usage map in the time-space domain) will bedeveloped. UEC will provide spectrum measurement based on RSRP (ReferenceSignal Received Power) extracted from multiple Android smartphones. The RSRPinformation can be used to plot the coverage map for the uO and hence providestatistical radio environment information which improves the handover and adaptivelycontrol the traffic bandwidth. Moreover, UEC will contribute to the design of spectrumdatabase and a spectrum management server for 5G-Enhance Trial 2. The collectedinformation. UEC main contributions to 5G-Enhance work packages are to WP2, WP3and WP5 as well as supporting WP6.
Fraunhofer Fokus (FHG) will contribute to the architectural design for network sharingat core network components. Mainly, FHG will operate the eMBB enhanced corenetwork components and the developed edge node components according to themobile micro operator case definition in Trial 2. Also, FHG will investigate differenttechniques to improve user experience and optimize bandwidth such as evolvedMultimedia Broadcast Multicast Service (eMBMS), link aggregation and TCP flowoptimization. Finally, FHG will support other partners by setting up the trail componentsin their testbeds. FHG main contributions to 5G-Enhance work packages are to WP1,WP2, WP4, WP5 and WP6.
• Ehime CATV is a local broadcast service provider in Japan and hence CATV willprovide support for Trial 2. CATV will contribute to the discussions related to the trialby providing feedback from the perspective of a local broadcast service provider toensure that the trial outcome satisfies their intended services. Also, CATV will provideequipment to support the trial such as fixed cameras, mobile cameras to be attachedat the helmet of the racers, the multi-angle broadcast servers and visualization app forthe trial. Also, CATV will provide local network infrastructure to assist with the trial localbroadcasting. Finally, CATV will act as a link with locals for trial organization purposes.CATV is mainly contributing to 5G-Enhance work packages WP5 and WP6 whileproviding assistance to WP2.
• JCTA Japan Cable and Telecommunications Association accelerates wireless servicebusiness in CATV industries in Japan. Together with Ehime CATV and RegionalWireless Japan, JCTA joined this project to contribute by providing experimentalopportunities.
• Regional Wireless Japan (RWJ) is a wireless service platform enabler assigned byJCTA. Cable operators including Ehime CATV use RWJ’s platform to offer MVNO, Wi-Fi, IoT and Regional BWA services. RWJ will support Ehime CATV in the discussionsrelated to the trial by providing feedback from the perspective of the candidate local 5Gservice enabler to ensure that the trial outcome is in line with cable industry’s wirelessstrategy.
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7.Summary and Conclusions
This is the second deliverable of 5G-Enhance WP2, hence it summarized the outcome ofactivities performed in Task 2.2 entitled “Unified technical requirements and specifications”,and specified in detail the 5G-enhance system requirements, specifications, architectures andused technologies that will be later implemented in project trials.
A brief outline of the two planned trials 3D remote streaming for a real-time surgery in EU andmulti-angle HD video streaming for an ad-hoc outdoor sport event in Japan is provided. Thenthe main technologies used in Trials 1 and 2 and how they improve on current systems. Thesystem hardware setup and configuration for the Trial 1 (real-time surgery stream) and Trial 2(race course stream) is discussed. Several technologies have been developed for 5G-Enhancewhich will have a signification impact on improving legacy solutions in dense eMBB scenarios.5G-Enhance is built over two key components, namely flexible and scalable network designand implementation and enhanced spectrum resource management. The technologiesinvolved include spectrum management, micro-operator, network management, vRANclusters, multicast and multi-connectivity.
A recap for use case scenarios and expected results in terms of KPI is given. The project usecases are categorized against the eMBB in 5G. The mapping between proposed technologies,trials and use cases shows a good alignment with eMBB use case in 5G.
Finally, from the work plan, we can conclude that WP2 is still on plan and on schedule.
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References
[3GPP-TR38.802] 3GPP, “Technical specification group radio access network; Servicerequirements for the 5G systems; Study on New Radio AccessTechnology; Physical Layer Aspects (Release 14); 3GPP TR 38.802V14.2.0, 2017.
[Aijaz_2018] Adnan Aijaz, “Packet Duplication in Dual Connectivity Enabled 5GWireless Networks: Overview and Challenges,”http://arxiv.org/abs/1804.01058v1, April 2018.
[Komulainen_2013] P. Komulainen, A. Tölli, and M. Juntti, “Effective CSI Signaling andDecentralized Beam Coordination in TDD Multi-Cell MIMOSystems,” in IEEE Transactions on Signal Processing, vol. 61, no. 9,pp. 2204-2218, May1, 2013.
[Mediatek_2018] Mediatek, “5G NR A new era for enhanced mobile broadband,”2018. [online] https://cdn-www.mediatek.com/page/MediaTek-5G-NR-White-Paper-PDF5GNRWP.pdf
[NGMN_2015] NGMN Alliance, “NGMN 5G White Paper,” 125 p., February 2015.
[Ternon_2014] E. Ternon, P. Agyapong, L. Hu, and A. Dekorsy, “Database-aidedenergy savings in next generation dual connectivity heterogeneousnetworks,” in IEEE WCNC’14, pp. 2811-2816, May 2014.
