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PROPRIETARY RIGHTS STATEMENT This document contains information, which is proprietary to the Flex5Gware Consortium.

Research and Innovation Action

Flex5Gware

Flexible and efficient hardware/software platforms for 5G network elements and devices

H2020 Grant Agreement Number: 671563

WP1 – 5G Architecture requirements, specifications, and use cases

D1.1 – 5G system use cases, scenarios, and requirements break-down

Contractual Delivery Date: December 31st, 2015

Actual Delivery Date: December 22nd, 2015

Responsible Beneficiary: EAB

Contributing Beneficiaries: EAB, CTTC, VTT, SEQ, ALUD, CEA, UC3M, CNIT, WINGS, TST, NEC, TI, UNIPI

Dissemination Level: Public

Version: V1.0

PROPRIETARY RIGHTS STATEMENT This document contains information, which is proprietary to the Flex5Gware Consortium.

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H2020 Grant Agreement Number: 671563 Document ID: WP1 / D1.1


Document Information

Document ID: WP1 / D1.1 Version Date: December 21, 2015 Total Number of Pages: 64 Abstract: This WP1 deliverable looks into use cases and top level

requirements for the Flex5Gware project. The outcome serves as basis for other WPs when doing the requirement break-down into tangible design targets used by the outlined 11 proof-of-concepts. The use cases are well aligned with prior art provided by technology leaders in the 5G community and illustrate how the targeted technical results in the project map to fundamental expectations of the 5G system. For each use case and number of relevant KPIs are derived, highlighting strategic challenges to be addressed in order to achieve wanted performance.

Keywords: 5G wireless communication, use case, network element, devices, versatility, flexibility, multi band, multi antennas, millimetre wave, system capacity, throughput, data rates.

Authors

Full Name Beneficiary / Organisation

e-mail Role

Fredrik Tillman EAB [email protected] Overall Editor / Section Editor / Contributor

Gian Michele Dell'Aera TI [email protected]

Section Editor / Contributor

Miquel Payaró CTTC [email protected] Section Editor / Contributor

Maria Fresia IMC [email protected] Contributor

Javier Valiño TST [email protected] Contributor

Pablo Serrano UC3M [email protected] Contributor

Apostolos Georgiadis CTTC [email protected] Contributor

Haesik Kim VTT [email protected] Contributor

Dieter Ferling ALUD [email protected] Contributor

Sylvie Mayrargue CEA [email protected] Contributor

Nikolaos Bartzoudis CTTC [email protected] Contributor

Marco Gramaglia UC3M [email protected] Contributor

Panagiotis Vlacheas WINGS [email protected] Contributor

Evaggelia Tzifa WINGS [email protected] Contributor

Aikaterini Demesticha WINGS [email protected] Contributor

Vera Stavroulaki WINGS [email protected] Contributor

Vassilis Foteinos WINGS [email protected] Contributor



Fabrizio Giuliano CNIT [email protected] Contributor

Ilenia Tinnirello CNIT [email protected] Contributor

Reviewers

Full Name Beneficiary / Organisation

e-mail Date

Maria Fresia IMC [email protected] 27.11.2015

Miquel Payaró CTTC [email protected] 27.11.2015

Gian Michele Dell'Aera TI [email protected] 27.11.2015

Pablo Serrano UC3M [email protected] 27.11.2015

Panagiotis Vlacheas WINGS [email protected] 27.11.2015

Sylvie Mayrargue CEA [email protected] 04.12.2015

Vincent Berg CEA [email protected] 04.12.2015

Tapio Rautio VTT [email protected] 04.12.2015

Dario Sabella TI [email protected] 18.12.2015

Michael Faerber IMC [email protected] 18.12.2015

Version history

Version Date Comments

V1 October 30th, 2015 First version of D1.1 based on the contents of IR1.1.



Executive Summary

This document is the result of the WP1 study on 5G system use cases, scenarios, and requirements. It covers the following objectives:

Established uses case families and specific use cases based on prior studies relevant to the over-all project objectives and targets

The definition of key performance indicators (KPI) and how these map to the use cases

Use case specific KPIs values and how the requirements relate to the overall performance

A summary of all project defined proof-of-concepts (PoC) and how they address targeted use cases

D1.1 is the first WP1 deliverable and will be used in other Flex5Gware studies going forward to set need requirements. This report also serves as a reference for the project evaluation where achieved performance will be benchmarked against stated targets. Besides the specific target fulfilment, maintaining the overall project objectives towards 5G use cases will be considered equally important.



Table of Contents

1. Introduction ..................................................................................................... 13

2. Target Scenarios and Use Case Definition ................................................... 14

2.1 Bandwidth definition ............................................................................................ 142.2 Use case families .................................................................................................. 14

2.2.1 Broadband access in dense areas ..................................................................... 152.2.2 Broadband access everywhere .......................................................................... 152.2.3 Massive internet of things ................................................................................... 15

2.3 Use cases .............................................................................................................. 162.3.1 Crowded venues ................................................................................................. 162.3.2 Dynamic hotspots ............................................................................................... 172.3.3 Smart cities ......................................................................................................... 182.3.4 Performance equipment ..................................................................................... 192.3.5 50+ Mbps everywhere ........................................................................................ 202.3.6 Connected vehicles (including Mobile broadband in vehicles and V2X communication for enhanced driving) ............................................................................. 21

2.4 Use case overview ................................................................................................ 22

3. KPI Definition ................................................................................................... 23

3.1 5G-PPP KPIs and Flex5Gware ............................................................................. 233.1.1 Performance KPI ................................................................................................ 243.1.2 Societal KPI ........................................................................................................ 253.1.3 Business-related KPI .......................................................................................... 27

3.2 Flex5Gware high level KPIs ................................................................................. 273.3 Use case KPI targets ............................................................................................ 31

3.3.1 Crowded venues ................................................................................................. 313.3.2 Dynamic hotspots ............................................................................................... 333.3.3 Smart cities ......................................................................................................... 343.3.4 Performance equipment ..................................................................................... 363.3.5 50+ Mbps everywhere ........................................................................................ 403.3.6 Connected vehicles ............................................................................................ 43

3.4 Flex5Gware KPIs at a glance and relationship to the work in other work packages ........................................................................................................................... 45

4. PoC and Use Case Mapping ........................................................................... 48

4.1 PoC overview ........................................................................................................ 484.1.1 On chip frequency generation ............................................................................. 494.1.2 Active SIW antenna systems for the 20-40 GHz band ....................................... 504.1.3 PAPR reduction and power amplifier pre-distortion ............................................ 514.1.4 Multiband transmitter .......................................................................................... 524.1.5 Full duplex FBMC transceiver ............................................................................. 524.1.6 High-speed low power resilient LDPC decoder .................................................. 534.1.7 HW/SW function split for energy aware communications ................................... 544.1.8 Reconfigurable programmable radio platform (terminal side) and SW programming performed and injected by the network .................................................... 554.1.9 Flexible, scalable and reconfigurable small cell platform .................................... 574.1.10 Flexible resource allocation in CRAN / vRAN platform ................................... 58



4.1.11 Multi-chain MIMO transmitter .......................................................................... 59

5. Conclusions ..................................................................................................... 60

6. References ....................................................................................................... 61



List of Figures

Figure 1-1: The WP1 work flow .............................................................................................. 13

Figure 2-1: Bandwidth definition ............................................................................................. 14

Figure 2-2: Dynamic hotspot traffic during a day (a) morning (b) afternoon (c) evening ................................................................................................................................... 18

Figure 2-3: Dynamic hotspots scenario in a train station (a) without train (b) with train ................................................................................................................................. 18

Figure 2-4: Use case families, use cases, and PoC mapping ................................................ 23

Figure 3-1: Example latency distribution from [Ull15] ............................................................. 37

Figure 3-2: Predicted average smartphone sales price between 2013-2017 ......................... 38

Figure 3-3: Forecasted spectral efficiencies in 2020 by ITU-R for RATG 1 (pre-IMT, IMT-2000 and its enhancements) and RATG 2 (IMT-Advanced) ................................... 41

Figure 3-4: Graphical representation of the relation between Flex5Gware WP1 and the work carried out in WP2, WP3, WP4, WP5, WP6. The depicted arrows between use cases, KPIs, and PoCs are just examples and are not meant to be exhaustive. ........................................................................................................................ 47

Figure 4-1: The PLL architecture (a) and its use in a receiver architecture (b). ..................... 50

Figure 4-2: Proposed Full-Duplex PoC Architecture .............................................................. 53

Figure 4-3: Proposed hardware for design validation ............................................................. 54

Figure 4-4: A high-level overview of the proposed architecture ............................................. 55

Figure 4-5: (1) WARP 802.11 architecture vs. (2) WMP WARP architecture ......................... 56

Figure 4-6: ISM coexistence (1) scenario, (2) TDMA approach, (3) frequency-bandwidth allocation ............................................................................................................... 57

Figure 4-7: Overall PoC Architecture ..................................................................................... 58

Figure 4-8: Flexible resource allocation in CRAN / vRAN platform overview ......................... 58



List of Tables

Table 3-1: 5G-PPP performance KPIs ................................................................................... 24

Table 3-2: 5G-PPP societal KPIs ........................................................................................... 25

Table 3-3: 5G-PPP business-related KPIs ............................................................................. 27

Table 3-4: List of Flex5Gware consolidated KPIs .................................................................. 28

Table 3-5: Relevance of Flex5Gware KPIs into the KPIs put forth by the 5G-PPP ................ 31

Table 3-6 KPI details for the Crowded venues use case ...................................................... 32

Table 3-7: KPI details for the Dynamic hotspots use case ..................................................... 34

Table 3-8: KPI details for Smart cities use case. .................................................................... 35

Table 3-9: KPI details for the Performance equipment use case. .......................................... 38

Table 3-10: KPI details for 50+ Mbps everywhere use case. ................................................. 42

Table 3-11: KPI details for Broadband in vehicles ................................................................. 44

Table 3-12: KPI details for V2X communications ................................................................... 45

Table 3-13: Flex5Gware KPIs at a glance .............................................................................. 46

Table 4-1: Association of the PoCs with use cases in Flex5Gware ....................................... 48



List of Acronyms and Abbreviations

Term Description

3GPP 4G 5G

3rd Generation Partnership Project Fourth Generation Fifth Generation

A/D Analogue to Digital

ADC Analogue Digital Converter

API BBU

Application Programming Interface Base Band Unit

BER BOM BS BW

Bit Error Rate Bill of Material Base Station Bandwidth

CMOS Complementary Metal-Oxide-Semiconductor

CoMP COTS CP CRAN CST CV

Coordinated Multipoint Commercial off the Shelf Charge Pump Comprehensive R Archive Network Cost Crowded Venue

DAC Digital Analogue Converter

DCF Distributed Coordination Function

DH DL

Dynamic Hotspot Down Link

DPD DSRC DVI

Digital Pre-distortion Dedicated Short Range Communications Digital Visual Interface

e2e End to End

EU European Union

FBMC Filter Bank Multicarrier

FDD FPGA FVR

Frequency Division Duplex Field Programmable Gate Array Flexibility / Versatility / Reconfigurability

GaN GPRS GUI

Gallium Nitride General Packet Radio Service Graphical User Interface

HD HW

High Definition Hardware

IC Integrated Circuit

ICT ID IF IN

Information and Communications Technology Identity Document Intermediate Frequency Intermediate Nodes

IoT Internet of Things



ISF ISM

Integration / Size / Footprint Industrial, Scientific and Medical

KPI LAT

Key Performance Indicator Latency

LDPC LLKPI

Low Density Parity Check Low-level KPI

LoS LPF

Line of Sight Low-pass Filter

LTE LTE-A M2M M-MIMO MAC

Long Term Evolution LTE Advanced Machine to Machine Massive-MIMO Media Access Control

MBV Mobile Broadband in Vehicles

MDV MGT MIMO

Mobile Data Volume Multi-gigabit Transceiver Multiple Input Multiple Output

mmWave Millimetre Wave

MTC MU-MIMO NGMN NoU NRE NRG

Machine Type Communication Multi-user MIMO Next Generation Mobile Networks Number of Users Non-Recurring Engineering Energy Efficiency

OBW OFDMA OPEX

Operation Bandwidth Orthogonal Frequency Division Multiplexing Access Operating Expense

PA Power Amplifier

PAPR Peak to Average Power Ratio

PFD PE

Phase-Frequency Detector Performance Equipment

PHY PLL

Physical Layer Phase Locked Loop

PoC PPP

Proof of Concept Public Private Partnership

QoS Quality of Service

R&D RAN RAT RATG

Research and Development Radio Access Network Radio Access Technology Radio Access Technology Group

RBW RES RF RRH RSU

Radio Bandwidth Resilience and Continuity Radio Frequency Radio Remote Head Road Side Units

RX SC Si

Receive Smart Cities Silicon



SIC Self-interference Cancellation

SME Small and Medium Enterprise

SW Software

TDD TDMA TOL

Time Division Duplex Time Division Multiple Access Test Object List

TX U-HDTV UDP UDR

Transmit Ultra High Definition Television User Datagram Protocol User Data Rate

UE UHD UL USRP V2X vRAN WAN WARP WCDMA WLAN WMP

User Equipment Ultra High Definition Up Link Universal Software Radio Peripheral Vehicle to Everything Virtualized Radio Access Network Wide Area Network Wireless Open-access Research Platform Wideband Code Division Multiple Access Wireless Local Area Network Wireless MAC Processor

WP Work Package



1. Introduction The overall objective of Flex5Gware is to deliver highly reconfigurable hardware (HW) platforms together with HW agnostic software (SW) platforms targeting both network elements and devices and taking into account increased capacity, reduced energy footprint, as well as scalability and modularity, to enable a smooth transition from 4G mobile wireless systems to 5G. The project is structured in 8 work packages (WP), where the first six are of technical nature and will primarily deliver technical results and findings. The final two WPs deal with dissemination and management and will monitor ongoing work according to the project description, as well as make sure the project outcome becomes visible and communicated in efficient ways in public forums. This deliverable, named “Use cases and scenarios for 5G systems” is the first output from WP1 and describes the targeted use cases and associated key performance indicators (KPI), and is intended to guide the technical work in WP2-5. The starting point has been the already outlined proof-of-concepts (PoC) in the project application which originate from fundamental 5G studies such as the METIS-I project [Oss14]. This is illustrated with the arrow marked 1 in Figure 1-1. In total 11 POCs were finally derived based on the project competence mix and realistic ambitions given the duration of 24 months. However, in order to find relevant KPIs, the PoCs had to be put in a context where overall requirements could be identified and broken down to relevant technical entities. This is visualized with the second arrow in Figure 1-1 where a selection of relevant use case families were identified, and based on those applicable use cases and KPIs outlined.

Figure 1-1: The WP1 work flow

The report is organized in three main sections where the first one (Section 2) describes the target use case families and use cases. The intention is to put the technical work into illustrative context without going into details. The second section (Section 3) looks into relevant metrics and needed technical performance for each use case based on assumed demands provided by background literature and reports. Finally, the last section (Section 4) provides a summary of the planned and committed PoCs, including how they map to targeted use cases.



2. Target Scenarios and Use Case Definition In this section we present how the outlined PoCs in the Flex5Gware project map into a use case structure and thus illustrate their importance for reaching the overall goals with the 5G system. There are numerous background studies made regarding scenarios and potential use cases, e.g. [Oss14], [Ela15], but in order to capture the most relevant ones from an implementation perspective (i.e., related to hardware and software platforms) we have decided to focus on three use case families described by the NGMN white paper [Elh15]. A family can be viewed as a consolidation of related use cases for a general scenario and in total the project will address 6 use cases with associated PoCs.

2.1 Bandwidth definition

The following bandwidth definition is used throughout the report. The radio bandwidth (RBW) describes the full RF bandwidth received or transmitted by a radio unit, e.g. a base station or user device. This measure accounts for all processed and used channels, but also potential gaps in between where interfering signals potentially could be located. The operational bandwidth (OBW) on the other hand tells the aggregated information bandwidth, i.e. the sum of all used channels inside the radio bandwidth. As a result OBW is correlated to the data rates and baseband capabilities, whereas RBW shows the radio agility and flexibility. In Figure 2-1 a fictive scenario is depicted for illustration purpose where the RBW amounts to 90MHz, but including two gaps of 20MHz each. Thus the OBW becomes 50MHz when summing the three channels.

Figure 2-1: Bandwidth definition

2.2 Use case families

As mentioned in the NGMN paper [Elh15], the use case families are not meant to be exhaustive with full coverage of all technical aspects related to 5G. The main scope is instead to show the needed flexibility and illustrate the wide span of different requirements posted by the aggregated use cases.



2.2.1 Broadband access in dense areas

This family captures the growing demand of services in urban and crowded places with a multitude of users requiring very high data rates. It ranges from business needs to human leisure, with the common denominator that many people in potentially small areas will launch and create large data streams simultaneously and expect a reliable and consistent service. We have decided to look into two specific use cases that capture two of the fundamental challenges associated with this family. The Crowded venues use case represents a situation where many users are temporarily located in an area where a single cell or multiple cells are already deployed. Cell capacity is a paramount capability as well as the uplink performance. The focus is also shifted from mobility to the reduced latency as users are stationary to a large extent. The second selected use case concerns Dynamic hotspots where the key feature is to handle momentary large crowds of people for occasional periods of time. One example would be a train station, where people getting off from arriving trains enter the platform at the same time and start using data services. Similar behaviours and situations may occur in many scenarios, such as sport events, concerts, random gatherings etc.

Main challenges associated with this use case family include primarily maximum system throughput and available peak data rates. This puts demanding requirements on the HW in terms of bandwidth and support of higher frequencies to enable such modes. Higher coding efficiency (e.g. LDPC) is looked into as well as support for massive-MIMO (M-MIMO) systems. In order to preserve network efficiency in a dynamic environment, measures related to time variant loads must also be addressed, as well as outlining the optimal split between HW and SW functionality in different modes of operation.

2.2.2 Broadband access everywhere

In order to provide a true mobile access experience, broadband data rates must be available everywhere, disregarding challenging situations where coverage is a problem, or when mobility might create undesired data stream interruptions. This use case family focuses on achieving this consistency and how to get enough performance close to cell borders in scarcely populated areas where a smaller grid size cannot always be used. Two use cases will be studied, 50+ Mbps everywhere and Connected vehicles; Mobile broadband in vehicles, putting demands on HW/SW flexibility, versatility, re-configurability, latency etc. These use cases do not represent any extremes themselves, but instead a minimum guaranteed level of service which from an implementation perspective is very challenging by nature.

2.2.3 Massive internet of things

A key feature in 5G networks is the handling of all connected devices, which is no longer a prediction, but something that is already happening today. Not only the number of connections will be demanding, but, more importantly, so will be the wide range of characteristics and expected service levels among all IoT products. To capture this plurality in an appropriate way, we have selected to address two use cases spanning from super low-cost sensors and actuators to highly capable devices such as tablets, handhelds, industry installations, etc.

The Smart cities use case will look into the massive deployment of urban IoT installations to enhance the quality of life (traffic assistance, environmental monitoring, etc.). As these devices will be deployed in billions, constraints on cost and low power are key parameters. On top, new concepts of integration need to be targeted to harmonize with a multitude of deployment surroundings as well as new paradigms of network injected SW as on-site installations and maintenance will practically be impossible.



The situation is different for the Performance equipment use case which targets high end products in terms of capabilities, such as data rate, processing power, and user interface. This use case brings similar challenges as found in the Broadband in dense areas family with focus on network throughput and end-user bit rates, but in addition it must also address power constraints and aggressive integration. The latter is especially pronounced for equipment whose mobility is a critical factor and geography agnostic network compliance paramount, i.e. unlimited roaming capabilities and standards support.

A different example of massive deployment in a mobile context is illustrated by the use case Connected vehicles: V2X communication for enhanced driving where driving assistance and safety are key components. Depending on the scenario, different qualities of the HW/SW implementation is in focus. Both the ability to handle non-continuous high bandwidth communication between vehicles (e.g. multimedia), as well as continuously monitoring and communicating low bandwidth vehicle related information at the same time will demand very flexible architectures. In the following section, the seven use cases related to the three use case families presented above will be described more thoroughly and give examples of how Flex5Gware will address key components of the overall challenges in 5G.

2.3 Use cases

2.3.1 Crowded venues

In urban dense areas, end users expect to have high capacity seamless connections to wireless services almost anywhere. User’s density and demands are variable: in a context of urban dense society, we consider crowded venues: there are some locations with massive crowds concentrated for some periods of time in small areas, (for public or sport events, concerts etc.). The kind of traffic is diversified: users can be interested on specific information during the event (scores, information about athletes or musicians etc.). Users can watch HD video, share live videos or post HD videos and photos on social networks. Differently from usual data rate estimation, considering the active usage of social networks in such venues, the heavy load sharing of HD video and photos is considered to be the main kind of traffic. For this reason the data rate is estimated to be higher in uplink rather than in downlink (UL data rate double than in DL, i.e., 50 Mbps and 25 Mbps respectively are foreseen). Stadiums and event halls (sport events or concerts), streets (sport events like for instance marathons, or other public events) have to be considered (so the propagation scenario is characterized by indoor, outdoor and indoor-outdoor propagation space). The connection density of this area is characterized by an average of 30000 users/km2 with peaks of 150000 users/km2 (e.g., in a stadium with a capacity of 30000 people). In order to serve such number of users, small cells able to connect to the self-configurable backhauling network have to be deployed. The reference network topology is represented by a self-configurable backhauling network, able to dynamically steer the required capacity towards the crowded venue. In addition, an efficient congestion control technique should be able to dynamically cope with such big numbers - in a stadium the traffic density reaches peaks of 3.75 Tbps/km2 in downlink and up to 7.5 Tbps/km2 in uplink. To ensure such peaks, the HW should be developed in the directions of integrating flexible full duplex mode (e.g., unified TDD/FDD frame structure design), taking then into account all the challenges related to design of advanced interference suppression techniques [Elh15]. A multi-RAT integrated solution that, depending on the kind of traffic, on the quality of service, and on the traffic load, can rapidly switch between different RATs and will be able ensure a uniform coverage and a better service for the users. The challenge of connecting to



the multiple RATs via reconfiguration will be addressed at the SW level so that the most appropriate RAT is selected according to the kind of traffic. One of the main technical challenges might then be the mmWave access link where there may be only a single path to the access point, obstructed by the crowds. From a mobility point of view, considering the massive crowds, it is straightforward to consider a low mobility level (pedestrian mobility).

2.3.2 Dynamic hotspots

The dynamic hotspot use case concerns the data traffic offloading in dense urban scenarios where in a limited space and time the network has to dynamically handle the presence of a high number of user connections. The network deployment in this use case is characterized by different coverage layers:

Macro layer: is used to guarantee the coverage over the entire served area and, in some implementations, to allow the transmission of a control layer with continuity. Because of their important behaviour these types of cells are rarely switched off. This layer is typically realized using high power transmitting nodes installed in high towers or on top of buildings. Low carrier frequencies can be used for the macro layer in order to exploit the better propagation characteristics of these waves.

Micro layer: is used to increase the network capacity in a small area where the number of users demanding high data rate can be high. This layer is typically realized using high number of low power transmitting nodes placed at moderate heights (e.g. 5 or 10 m) in order to be as close as possible to the served users. This layer can be used to boost the amount of data transmitted to the users using more efficient transmission techniques (e.g. exploiting modulation with higher cardinality, and/or with the introduction of beamforming techniques).

In a dense urban scenario, the users are typically not uniformly distributed over the coverage area, but they are grouped with higher probability in some places called hotspots. The hotspot is a limited region of the coverage area where the amount of requested network capacity is larger with respect to the average network capacity requested in the entire scenario. The typical positions of these traffic hotspots could be train/bus station, business centre, schools, shopping malls, parks, squares or other popular place in a city. These hotspots are densely populated only for a limited period of the day, while in the rest of the day the requested capacity is similar to the majority of the urban locations. In order to explain this phenomenon Figure 2-2 shows an example of the user traffic distribution during the day: in the first part of the day (a) the majority of the traffic is concentrated in the business centre, at the train/bus station or in the places used by people to reach work/school locations; in the second part of the day (b) the user traffic is concentrated in the park and shopping malls or in other places reached by the people after work/school; in the last part of the day (c) the city centre or restaurant district are reached by the majority of the people.



Figure 2-2: Dynamic hotspot traffic during a day (a) morning (b) afternoon (c) evening

The previous example describes how the hotspots can dynamically appear and disappear during a day in a couple of hours. This represents a slow dynamic hotspot activation/deactivation, but also faster dynamic hotspot activation/deactivation takes place in a dense urban coverage scenario. In Figure 2-3, it is shown how the hotspots dynamic activation/deactivation can follow the users movement in a train station: in (a) no trains are at the platforms and the majority of the persons are in the train station shopping area or at the coffee bar located in the station; (b) when a train arrives at the platform, a large amount of traffic is generated by people getting off the train and stopping at the platform, looking for their relatives or for generic information on their final destination.

Figure 2-3: Dynamic hotspots scenario in a train station (a) without train (b) with train

This second example describes how also in a more limited scenario the location of the generated traffic can change dynamically. In this case the hotspot activation/deactivation time has to follow the duration of train stop at the platform and the frequency of the train arrivals/departures. Other examples of dynamic activation of hotspot are: when a traffic jam is caused by a car crash or another event generating an unexpected growth of resources demand, or during the break time in a school/university, where it is possible to identify a dynamic traffic hotspot activation/deactivation following the movements of the students.

2.3.3 Smart cities

Both the R&D community and the local authorities in cities are more and more interested in keeping track of all relevant and measurable activities inside the city. This is impacting the number of already deployed elements controlling key parameters and making use of the cellular network to send the acquired data to data processing servers on the Internet.



A smart city, as it is seen now, is a collection of everyday life services envisaged to improve citizens’ life in a great variety of situations. Efforts to identify, classify, and propose measurable KPIs depending on selected scenarios have been made, as for instance on the FP7 project CityPulse [CiP15], where up to 101 scenarios were proposed. Depending on the selected scenario, key parameters such as security, coverage, number and density of devices, availability, scalability, energy efficiency, network processing, or coverage might rise as critical, while others might be less of concern. Thus, application developers and scenario designers should carefully take into account the special needs of each envisaged use case. The Flex5Gware project views this use case as a particularization of the massive IoT family where a great amount of small, cheap, and energy efficient devices are placed all over the city and use the cellular network for communication purposes, either on a direct way (sensors transmitting data directly to the network) or using a gateway/concentrator to relay the info on their behalf. More precisely, at least the following applications are covered by this use case:

Environmental monitoring. This is the most commonly adopted application on smart cities. It is relatively simple and cheap to place environmental sensors measuring temperature, humidity, pollution, noise, wind strength and direction, rain, solar radiation etc. to provide information to citizens. In order to provide accurate measurements and characterize the whole city, they must be densely distributed covering all inhabited surfaces.

Vehicle and human detection. It is very useful to detect traffic patterns or citizen behavior in key places inside the city to be able to early react to congestion situations, as well as for accident prevention and traffic protection. For example, roads experiment predictable traffic jams and, if the data is properly processed, preventive and mitigation actions can be automatically triggered.

Any other potential application can also be covered in this use case. The basic assumption is that the city will be full of devices, measuring data and sending them to the network. However, Flex5Gware intends to primarily use the aforementioned applications as part of the use case.

2.3.4 Performance equipment

Among all connected devices in the networked society, a fair amount will be more than just simple sensors or actuators as the ones described in the previous section. These devices are designed and benchmarked according to performance metrics that go beyond IoT baseline, e.g. power consumption and cost, and target both consumer markets and industry applications. The HW will to a large extent be uniform across a multitude of product segments to cope with cost pressure. Differentiating factors will mainly reside in the SW domain where fast time-to-market allows for penetration without overwhelming investments. It is important to realize that innovation and platform investments for high performing devices will mainly occur in the cost driven consumer market thanks to superior volumes and cost structure. Customized platform development for specific industrial needs will only happen in specific areas where cost awareness is less important or special needs makes COTS products hard to use (military grade devices, space travel equipment etc.). However, piggybacking on COTS HW and consumer market SW does not make the industry device ecosystem irrelevant or remove custom requirements. Communicating equipment in a factory will for instance indeed impose challenges in terms of latency, reliability, integrity (cryptology) despite being very similar in platform architecture. And in local areas (e.g. a production floor) the device density can be equally large as found in consumer hotspots. So what are the key attributes and differences if we compare consumer and industry equipment deployed in 5G networks? The NGMN whitepaper [Elh15] outlines DL and UL in



the range of 300 Mbps and 50 Mbps respectively (peak rates) and targets mobility up to 500 km/h in train scenarios, but with lower service to some extent. Many of these performance metrics related to modem capabilities will be developed and driven by UE platform manufacturers targeting the full market. However, as the device appearance and form factor may differ significantly between segments it opens up for customization in terms of display GUI, cooling, battery size, antenna solutions etc. Another key difference is the higher layer SW where full customization is expected. Besides basic functionality inequalities, which are not necessarily 5G parameters, aspects related to network security may be challenging demands from industry applications. Especially as cloud services will replace locally operated data centres and sensitive commercial grade data traffic will share networks with the open consumer market.

2.3.5 50+ Mbps everywhere

The 50+ Mbps everywhere use case concerns the situation where users require very high data rates always and everywhere, which is specially challenging in areas with sparse network infrastructure, such as scarcely populated areas, rural and even in some wide suburban areas. Human users are generally the main target of this use case, which has to support thus a large diversity of services, large file downloading and video streaming being two illustrative examples. A consistent user experience with respect to the achieved data rate needs a minimum guaranteed throughput everywhere. As it is emphasized in [Ela15], [Elh15], the minimum target value of 50 Mbps everywhere refers to the minimum user data rate that every user should experience and, therefore, must not be misunderstood by the theoretical peak rate that a user may experience. In addition, this use case strives at bringing the same minimum throughput experience for an end-user on the move, as for the users at home or in the office. Consequently, in this use case, reliable communication is also driven along with low energy consumption, which is a common KPI within Flex5Gware. The importance of energy consumption reduction to enhance the battery lifetime of terminal devices and to reduce the OPEX of base stations is of paramount importance in areas with low coverage due to higher propagation losses. In this setting, HW/SW technologies that enable a more efficient operation of the transmitter, such as PAPR reduction strategies combined with digital pre-distortion and envelope tracking techniques will play a major role in the years to come. At first sight, cell densification seems to be a key solution for guaranteeing such minimum throughput in future urban environments. The ubiquity required on such small cell deployment poses significant constraints on the requirements of small cells, as they will have to be low-energy and low-cost and be based on virtualized scalable software. This latter feature will allow the small cell platform to be shared by multiple tenants. However, cell densification will have to be complemented by wide coverage solutions as well as flexible, energy and cost efficient solutions that must also be developed to provide ubiquitous coverage with throughput guarantees in suburban and rural areas. For example, the CRAN/vRAN heterogeneous network architecture is a strong candidate solution to this problem. This kind of distributed architecture allows to implement resource allocation algorithms based on, e.g., dynamic Radio Remote Head (RRH) activation/deactivation and Base Band Unit (BBU) allocation and association with RRH that enable an energy and cost-efficient operation. Moreover, in this respect, the ability to accurately estimate network conditions and dynamically adapt to them is crucial to optimise user throughput while making an efficient use of the resources. The optimisation should build on context estimates (e.g., position estimates, interference, signal quality) to modify, in real time, the operation of the RAT, to adapt it to context variations and sudden changes in the scenario to maintain the user rate above the threshold. E.g., in situations where a very high data rate (e.g., 500 Mbps) access will likely fail (non-line of sight or raining conditions) instead of wasting power trying to re-establish the connection and losing data packets in the process, the 5G device will be able



to automatically (and efficiently) connect to the base station using a more robust, less performant RAT which will most likely succeed and still keep the throughput above 50 Mbps. Consequently, in addition to the user data rate, this use case puts hefty requirements on the re-configurability capabilities of HW solutions both at the base station and at the user terminal. For example, it is crucial to provide multiband, low-cost transceivers that are able to operate at multiple bands depending on the exact communication needs. Finally, it is important to highlight that the requirement of guaranteeing a minimum rate of 50 Mbps everywhere (or even 100 Mbps as it is often pointed out in [Ela15][Elh15]) directly impacts the operation bandwidth that will need to be supported at the terminal side. Assuming that a certain spectral efficiency, ε, can be achieved [Itu13], the required operation bandwidth BW is given by:

where R is the rate requirement (e.g., 50 Mbps or 100 Mbps). This operation bandwidth will be the minimum maximum bandwidth that all terminals should be able to support, i.e., terminals might support bandwidths well above that, but, at least, they should be able to support this “minimum maximum bandwidth” mode. More details on this issue are given in Section 3. A potential solution to alleviate this bandwidth requirement is to increase the achievable spectral efficiency by means of, e.g., MIMO operation (multiple antennas would be required at both at base station and at the terminal). Thus, given that a higher number of antenna elements are expected at the base station, improvements in integration, size, and cost for multi-antenna implementations of the base station transceiver will be HW enhancements required to achieve a successful application of this use case.

2.3.6 Connected vehicles (including Mobile broadband in vehicles and V2X communication for enhanced driving)

In the Connected vehicles use case, there are two types of traffic that have to be supported in 5G networks. On one hand, we have the “mobile broadband” traffic, triggered by humans and currently most prevalent in mobile devices. It poses the same set of requirements, but now in the challenging scenario of mobile vehicles (due to speed, vehicle plating, etc.). On the other hand, the “machine initiated” traffic, is focusing on to support driving or enable automatic driving, and therefore introduces a different set of requirements due to its nature. Indeed, Machine-to-Machine communication cannot be characterized with a fixed set or requirements, as these vary according to their nature (e.g., IoT devices vs. V2X communication). Due to these two types of traffic which are very different in nature, the Connected vehicles use case is divided into two use cases: Mobile broadband in vehicles and V2X communication for enhanced driving. Concerning the mobile broadband traffic, as hinted above the requirements should be aligned with those of the other use cases studied in Flex5Gware, although the means for the actual provision of the service should be adapted to the specifics of the highly-mobile, highly-varying (in terms of density) scenario. For the case of “machine triggered” traffic, there are three main types of application that are in the class of service related to 5G V2X communication:

Vehicle to Vehicle: collision avoidance, autonomous driving, vehicle platooning Vehicle to Pedestrian: collision avoidance Vehicle to Infrastructure: fast dissemination of emergency information



In order to support these types of services, 5G networks should take into account:

The (very-high) mobility of the scenario, and its heterogeneity - For Vehicle to Infrastructure communications, seamless connectivity with

guaranteed QoS is a notable challenge, given that vehicles are travelling at high speeds and they are typically characterized with very different behaviours.

- For Infrastructure to Vehicle communications: some kind of location control capabilities have to be implemented to enable controlled geo broadcasting.

For the case of Mobile broadband, the extra attenuation caused in propagation, as receivers are placed inside the vehicle, and thus the metal introduces around 10 dB of additional losses. For the case of V2X communication, this is not the case as hardware is designed for this type of scenarios.

The availability of multiple RATs: it is envisioned that vehicles will be provided, at least, with two different RATs, one to connect to the cellular network, and another for Dedicated, Short-Range Communications (DSRC).

Among other challenges, some of the key research questions are:

How to tune the operation of the different RATs to adapt them to the conditions of the use case? For instance, for the case of Mobile broadband, various devices inside a vehicle may rely on device-to-device communications [Asa14] to operate more efficiently. For the case of enhanced driving, standards such as 802.11aa [Sal14] should be looked into, to enable efficient real-time streaming.

How to combine the cellular and DSRC to obtain the best coverage and provide QoS for critical applications (considering not only the client side, but also the network side)? Along these lines, it could be interesting to explore novel dissemination techniques (e.g., Floating Content [Ali14]) to extend the regular operation of 802.11 [Hie10].

2.4 Use case overview

As an illustration how the use cases connect to the use case families, an overview is provided in Figure 2-4. In line with Section 2.3.6, Connected vehicles will be mapped to both Broadband access everywhere and Massive internet of things, and thus relate to different PoCs. As seen, all uses cases will be addressed by at least two PoCs and the spread is close to an even balance. A small bias towards Dynamic hotspots is foreseen to happen, but given the nature of this scenario and its vital role for 5G systems, this is regarded as a natural consequence.



Figure 2-4: Use case families, use cases, and PoC mapping

3. KPI Definition In the previous section, the Flex5Gware use case families and use cases have been outlined according to the activities that were defined in Task T1.1 “Use cases and scenarios for 5G systems”. These use cases will put specific requirements on HW/SW platforms for 5G via a set of high level KPIs that will be associated to each use case and that will be defined and quantized in this section, following the activities defined in Task 1.2 “5G system requirements break-down”. However, before delving into the definition of Flex5Gware KPIs, the 5G-PPP high level KPIs will be first presented to provide the appropriate framework for the planned contributions of Flex5Gware. 3.1 5G-PPP KPIs and Flex5Gware On December 17, 2013 the EU Commission and the 5G Infrastructure PPP signed the PPP Contractual Arrangement [EUC13], which, among other aspects, describes the high-level KPIs of the PPP for the period starting in 2014 and finalizing in 2020. In this context, as one of the different funded projects within the 5G-PPP, Flex5Gware’s planned contributions constitute a step forward towards achieving those KPIs. In the following three subsections, the 5G-PPP KPIs described in [EUC13] that are relevant to the Flex5Gware project are presented divided in performance, societal, and business-related KPIs. Moreover, for each 5G-PPP KPI, a qualitative assessment of the relevance of that KPI in relation to the contributions provided in Flex5Gware is also provided together with details on the planned Flex5Gware contribution towards the achievement of the KPI. Finally, observe also that 5G-PPP KPIs that are not addressed by Flex5Gware are not included in the sections that follow.



3.1.1 Performance KPI

Table 3-1: 5G-PPP performance KPIs

KPI Relevance (High/Medium/ Low)

Details on planned project contribution towards achieving the KPI

P1 Providing 1000 times higher wireless area capacity and more varied service capabilities compared to 2010.

High Flex5Gware provides a three-fold contribution towards achieving higher wireless capacity: 1) developing communication platforms that enable the operation in additional frequency bands, including mmWave, which remarkably increase the operation bandwidth both at system and user levels; 2) improving existing wireless technologies to increase the data volume per geographical area by improving the typical user data rate and by enhancing the number of devices that can be connected at any given time; and 3) handling of the resulting huge amount of available spectrum via the design of resource allocation and management policies for highly dense scenarios.

P3 Facilitating very dense deployments of wireless communication links to connect over 7 trillion wireless devices serving over 7 billion people.

High Flex5Gware contribution in increasing the number of connected devices will be achieved via five different approaches: i) increasing the overall simultaneously operated bandwidth (via specific HW improvements that include the use of mmWave spectrum), ii) reducing the required bandwidth for a given user data rate (e.g., via full duplex operation), iii) allowing more users per spatial area (e.g., by supporting massive MIMO architectures that can increase the spatial reuse thanks to beamforming), iv) addition of small cells that can offload traffic (thanks to the optical RF to the antenna technology) and, finally, v) optimizing the medium access control protocol so that users can access the medium more efficiently (e.g., thanks to the dynamic re-configuration of the MAC layer).

P4 Creating a secure, reliable and dependable Internet with a “zero perceived” downtime for services provision.

Low In Flex5Gware, reliability of Internet connectivity will be improved by addressing resilience and continuity. This will be achieved through two main contributions: 1) the SW platforms developed in Flex5Gware will have the capabilities to select the most appropriate RAT among the plethora of possibilities offered by 5G depending on the particular scenario and propagation conditions in such a way that the service



resilience and continuity is guaranteed (i.e., by allowing to choose a less performant RAT in terms of rate, but whose resilience is higher, or by choosing to use the massive MIMO capabilities to improve the link quality instead of improving the user rate). 2) Also, thanks to the multi-node coordination layer that will be developed within Flex5Gware, the reliability will be improved from a network-wide perspective rather than from a single link point of view.

3.1.2 Societal KPI

Table 3-2: 5G-PPP societal KPIs

KPI Relevance (High / Medium / Low / N.A.)


S2 Reduction of energy consumption per service up to 90% (as compared to 2010);

High In the reduction of energy consumption, Flex5Gware contribution can be divided into two main areas: i) improving the efficiency of the HW (e.g., thanks to the design of novel access mechanisms oriented to the energy needs of MTC devices and enabling the creation of low power and low cost cellular modems) and ii) improving the way energy is spent at SW level (thanks to energy-aware SW APIs and virtualization / reconfiguration control functionalities).

S3 European availability of a competitive industrial offer for 5G systems and technologies;

High Flex5Gware addresses this aspect by targeting a reduction of the cost and increasing the resource usage efficiency of 5G HW/SW platforms.

Regarding the reduction of cost, Flex5Gware contributions will have a significant impact on the cost of 5G handheld devices and network elements (e.g., base stations) via cost reductions on their HW components. The impact of decreasing the HW platform cost is especially remarkable in 5G where the number of communicating nodes is expected to be unprecedentedly large. Flex5Gware will conduct research and demonstration on low cost architectures and components ranging from the use of advanced semiconductor materials (e.g. GaN-on-Si) for reduced costs together with low-cost joint antenna and power amplification units (based on SIW technology) to low-cost on-chip frequency generation system in 28 nm monolithic radio



CMOS system for mmWave band radios. In addition, Flex5Gware will make significant contributions to reducing the network deployment cost via, e.g., the use of remote antennas (which can save on utilities like building space), the re-configurability capabilities of the HW, which reduce the quantity of HW elements, and, finally, the enabling of infrastructure multi-tenancy via improvements on the virtualization potential of network elements.

Regarding the resource usage efficiency, Flex5Gware proposes technology solutions that improve the energy and spectrum efficiency and also reduced latency (time). Clearly, time, spectrum and energy will be the most important resources that 5G will need to efficiently handle to avoid the spectrum crunch and to sustain the scalability of the network. Flex5Gware will address its efficiency via, e.g., (i) the use of PAPR reduction and linearization techniques that enable the PAs to operate using higher energy efficiency modes, (ii) the design of HW architectures that will support full duplex and the transmission/reception of spectrally efficient waveforms such as FBMC, or (iii) the design of energy-aware interfaces, control and management plane tools and flexible SW solutions for centralized RAN environments that offer energy efficiency through coordination and dynamic reconfiguration.

S4 Stimulation of new economically-viable services of high societal value like U-HDTV and M2M applications;

High Flex5Gware addresses this aspect via stimulation of M2M applications and, more precisely, sensor based M2M applications. In the context of digital HW/SW domains, in Flex5Gware, HW-agnostic APIs that will be enhanced by sensor-retrieved context awareness will be provided in order to enable the (re)configuration and management of reconfigurable HW devices in terms of multiple programmable radio interfaces, sensors, other resources (e.g. storage, battery etc.) in an optimal and scalable manner. These APIs comprise a generic front-end for the communication with the HW-agnostic SW and a generic back-end for the communication with the actual HW. The generic front-end is accessed through appropriate authentication/access control mechanisms, especially when the reconfigurable HW is intended to be used across multiple SW domains. Precisely, one



of the proof-of-concepts that will be demonstrated within Flex5Gware is entitled “Reconfigurable programmable radio platform and SW programming performed and injected by the network”. As it has been pointed out, this PoC encompasses multiple programmable radio interfaces, exposing a common set of API for configuring it, together with a set of sensors (gyroscopes, accelerometers, temperature, humidity, pressure, etc.). Thus, this PoC developed in Flex5Gware can be used as the platform that will enable the deployment of these novel sensor based M2M applications.

3.1.3 Business-related KPI

Table 3-3: 5G-PPP business-related KPIs

KPI Relevance (High / Medium / Low / N.A.)


B2 Target SME participation under this initiative commensurate with an allocation of 20% of the total public funding;

Medium The percentage of public funding devoted to SMEs is expected to increase in the successive phases of the 5G-PPP. This is due to the fact that later phases will be addressing technology areas closer to market needs, whereas initial phases are more research oriented. Nonetheless, even in this first phase, the percentage of the total budget devoted to SMEs is 14 % (18 % in terms of effort)

B3 Reach a global market share for 5G equipment & services delivered by European headquartered ICT companies at, or above, the reported 2011 level of 43% global market share in communication infrastructure.

High The proposed advances in HW/SW platforms of Flex5Gware (including critical elements of communication networks) are clearly aligned with the future needs of 5G networks and systems and, thus, will undoubtedly lead to a wider range of opportunities in new markets for the industry partners of Flex5Gware that will contribute to ensuring that it stays above 43 %.

3.2 Flex5Gware high level KPIs In order to be able to provide quantifiable contributions from the Flex5Gware project towards the achievement of the 5G-PPP KPIs described in the previous section, the first activity within Task 1.2 “5G system requirements break-down” has been to define and quantize a set of high level KPIs, that, in the following, will be referred to as Flex5Gware KPIs.



Given the wide scope of the research topics addressed in Flex5Gware, these derived high level KPIs will then be particularized in different tasks outside WP1 for each one of the four technology areas addressed in Flex5Gware (each one corresponding to one work package):

WP2: RF front-ends and antennas WP3: Mixed-signal technologies WP4: Digital front-ends and HW/SW function split WP5: SW modules and functions

These particularizations will yield to specific design principles, requirements, and guidelines for the development of the corresponding enabling technologies in each one of those areas. These particularizations are especially important in this initial phase of the 5G PPP because they will set the starting point upon which all the technology developments will capitalize. Thus, it was of paramount importance for the proper development of the Flex5Gware project activities to choose a set of high level KPIs that adequately capture the requirements expected from 5G communication platforms for the subset of use cases described in the previous section and that, also very importantly, allow to prove the level of fulfilment towards achieving the 5G-PPP KPIs described in Section 3.1. Discussions started on which should be the list of high level KPIs, both internally, at consortium level, but also externally with other 5G-PPP projects, e.g., via the attendance to the “5G-PPP Cross-project Workshop on Scenarios, Requirements, Performance Evaluation, Spectrum and RAN Design Assumptions” organized by the Metis-II project. The outcome of these discussions, the so-called “Consolidated KPIs” is presented in Table 3-4 together with an explanation on the meaning of each KPI and how Flex5Gware intends to tackle it.

Table 3-4: List of Flex5Gware consolidated KPIs

KPI Acronym Description and related Flex5Gware approach

Flexibility / versatility / re-configurability

FVR

The definition of this KPI has a quite broad coverage (which will be particularized in each relevant use case), but it is related to the 5G requirement of an increase on the number of functions that a certain HW or SW module can perform. Within this context, the terms flexibility, versatility and re-configurability have rather similar meanings and can even sometimes be used interchangeably. However, whenever a very precise meaning is necessary, we will refer to flexibility to denote the ability to cope with variable circumstances; versatility for having varied uses or serving many functions competently; and, re-configurability for the ability to self-rearrange elements or settings (e.g., of a certain HW or SW module). Thus, within a fine level of detail, the term flexibility is the more general one and incorporates both versatility and re-configurability as particular cases.



For example, Flex5Gware will deliver new approaches on versatile multi-band transceiver implementations that will result in RF base station key elements enabling operation bandwidths of 1 GHz (gain factor of 10 with respect to current technologies).

Cost CST

The cost KPI is defined as the expenditure of resources, such as time, materials or labor, for the attainment of a certain HW or SW module. Flex5Gware contributions will have a significant impact on the cost reduction with respect of the state-of-the-art of 5G handheld devices and network elements (e.g., base stations) via cost reductions mostly based on their HW components. The impact of decreasing the HW platform cost is especially remarkable in 5G where the number of communicating nodes is expected to be unprecedentedly large. Flex5Gware will conduct research and demonstration on low cost architectures and components ranging from the use of advanced semiconductor materials to low-cost on-chip frequency generation for mmWave band radios.

Energy efficiency NRG

This KPI is related to the energy consumption reduction of terminal devices and network elements and to the improvement of performance while keeping the energy consumption at the same level. The most common metric that is used to characterize this KPI is the reduction in the consumed Joules per delivered bit. This KPI can be one-to-one mapped to the 5G-PPP KPI S2. Thus, Flex5Gware approach towards that KPI is already described in Table 3-2.

Resilience and continuity

RES

The resilience and continuity KPI refers to the probability that a certain amount of data is successfully delivered to its destination within a given time frame. This KPI is especially relevant in wireless environments due to, e.g., the rapidly changing nature of the propagation conditions. Within the Flex5Gware project, this KPI can be one-to-one mapped to the 5G-PPP KPI P4. Thus, Flex5Gware approach towards that KPI is already described in Table 3-1.

Mobile data volume

• Aggregated data rate

• Coverage / ubiquitous access

MDV

This KPI deals with the aggregated cell capacity in both the uplink and the downlink within a given geographical area. Moreover, when particularized to a single cell and its coverage area, it can also be related to cell edge performance (expressed in terms of guaranteed minimum data rates at the cell edge). Given its definition of aggregated data rate divided by a given area, this KPI is compound. Thus, Flex5Gware contributions toward this KPI can either be aimed at increasing the aggregated data rate (e.g., via increasing the user data rate or the number of users, see the UDR and NoU KPIs) or also by reducing the coverage area by increasing the cell access points via, e.g., small cell



deployment. In this latter example, Flex5Gware will contribute with the demonstration of multi-tenant, low-energy and low-cost small cell base stations based on virtualized scalable software.

Number of users / connected devices

NoU

The number of users / connected devices KPI refers to the number of devices that are connected to the network via one or multiple access points while satisfying a certain quality metric that can be related to some other Flex5Gware KPI (e.g., user data rate, latency, etc.). Although this KPI has clearly an impact on 5G-PPP KPI S4 (Table 3-2), the Flex5Gware contribution to the number of users KPI can be directly linked to the 5G-PPP KPI P3. Thus, Flex5Gware approach towards that KPI is already described linked to P3 in Table 3-1.

Bandwidth

• Radio bandwidth

• Operation bandwidth

BW

This KPI is related to the bandwidth supported by both network nodes and UE/sensors/actuators. As it has been pointed out before, the radio bandwidth (RBW) describes the full RF bandwidth received or transmitted by a radio unit, whereas the operational bandwidth (OBW) refers to the sum of all used channels inside the radio bandwidth.Flex5Gware addresses aspects related to this KPI by, e.g., multi-band operation, fast A/D converters that operate at huge bandwidths, and the enabling of operation at mmWave bands.

Latency LAT

This KPI relates to the network latency (round trip time) and to the link latency, which is measured as the time between a packet being available at the transmitter and the availability of this packet at the receiver (which takes into account, e.g., constraints and delays imposed by the HW). Flex5Gware will provide solutions for 5G communication platforms so that the latency can be reduced via the development of HW architectures that will support flexible waveforms. In addition, the dynamic HW/SW function split together with the Analogue/Digital signal processing trade-off considered in Flex5Gware will also contribute to reducing latency via choosing configurations that trade energy consumption with latency. Other contributions of Flex5Gware designed to reduce latency are represented by the development of very fast and multiband A/D and D/A converters, which give additional degrees of freedom at system level to reduce latency when the bandwidth is increased.

User data rate UDR

This KPI relates to the achieved end user (e.g., handheld for human traffic, device for MTC, etc.) data rates (both UL and DL) in different forms: peak, average or minimum guarantee. For example, Flex5Gware will contribute to increase the typical data rate by: i) increasing the user data rate per spectrum unit (e.g., via full duplex operation, the HW support for 5G waveforms like FBMC, and faster FEC decoding architectures), ii)



increasing the user bandwidth (via, e.g., multi-band operation, fast A/D converters that operate at huge bandwidths, and the enabling of operation at mmWave bands), and iii) reducing the experienced interference (e.g., through dynamic basestation coordination and/or massive MIMO transmissions).

Integration / size / footprint

ISF

This KPI is related mostly to the HW footprint related to its size/volume, but also on the SW design implications on the digital HW (e.g., via the need of additional integrated memory due to the size of the SW programs). In Flex5Gware, this KPI is addressed e.g., via co-integration of an on-chip frequency generation system in monolithic radio SoCs (system on chips), where signal integrity is important or also via the co-integration of power amplifier and antennas in the range of 20 to 40 GHz in nanometre CMOS technologies for small-cell electronics.

From the definitions and descriptions provided in the table above, a relation between the Flex5Gware KPIs and those from the 5G-PPP can be established, which is summarized below:

Table 3-5: Relevance of Flex5Gware KPIs into the KPIs put forth by the 5G-PPP

5G-PPP KPIs P1 P3 P4 S2 S3 S4

Fle

x5G

war

e K

PIs

FVR X X CST X NRG X RES X MDV X NoU X X BW X X LAT X X UDR X ISF X

Thus, by tracking the progress achieved in Flex5Gware in each one of the Flex5Gware KPIs, it will be straightforward to track the progress according to the 5G-PPP KPIs. In the following section, we provide the KPI target figures targeting the 2020 time frame for each one of the use cases identified in Section 2. It is important to highlight that, out of the 10 Flex5Gware KPIs, each use case will only address those KPIs that are relevant under the specific circumstances of the use case.

3.3 Use case KPI targets

3.3.1 Crowded venues

For the Crowded venues use case, the most challenging KPI is represented by the ultra-high number of users (NoU). In case of very dedicated areas/structures, most of the time the load may be relatively low with few ultra-heavy traffic peaks during the day. The number of



users of this area is characterized by an average of 30000 users/km2 with peaks of 150000 users/km2 (e.g., in a stadium with a capacity of 30000 people). All the other KPIs become critical when connected with the foreseen number of users. For example, the user data rate (UDR) is estimated to be on average 50 Mbps in upload and 25 Mbps in download, target values that cannot be considered as extremely challenging for a limited amount of users (although the UL data rate is currently available only as a peak UL and not in average). On the other hand, considering the users foreseen in a stadium, these numbers drive the mobile data volume (MDV) to reach peaks of 3.75 Tbps/km2 in downlink and up to 7.5 Tbps/km2 in uplink, which are challenging values that cannot be supported by the current technology. Same consideration can be done for the requirement on latency (LAT): considering the real time sharing of multimedia contents, latency below 10 ms is expected. This requirement can be currently fulfilled in a 2-way RAN, but, when coupled with the huge amount of users to be served, it becomes really challenging. Also the re-configurability (FVR), that takes into account the time needed to efficiently switch on-off additional access points (needed when the events are taking place) or to reconfigure the network in case of failure (and then ensure a uniform coverage and a high QoS) plays a critical role when such amount of users is considered.

Table 3-6 KPI details for the Crowded venues use case

Acronym Requirement Comments and gap to currently available

FVR Less than 30 s

In order to serve such amount of users efficiently, fast and efficient re-configurability is required, in order to guarantee a high quality of service in case of access point failures or new access points added on traffic request base.

RES 95 % (std for 5G)

Required only for the specific time of the event. Although the required resilience is standard for 5G, considering the amount of traffic, this becomes a not negligible KPI. RAT flexibility, depending on the kind of traffic and on the network load is fundamental to ensure such level of reliability.

MDV

Peaks DL: 3.75 Tbps/km²

(DL stadium: 0.75 Tbps/km²)

UL: 7.5 Tbps/km²

(UL stadium: 1.5 Tbps/km²)

This is the connection density foreseen multiplied for the user experience data rate. The current technology cannot support such capacity

NoU

Peak of 150000 users/km2

(average users in a stadium: 30000 users/stadium)

In case of dedicated areas/structures, there may be heavy traffic peaks during the events, but the average load is lower. In a stadium (0.2 km2) the average number of active users is computed considering that in a stadium with capacity 100000, 30 % of users are active [Elh15]. Currently LTE systems can handle around 2000 users/km2 – but at much lower cell-edge rates [Elh15].



BW 3 GHz UL

1.5 GHz DL (OBW)

Considering as the Peak the stadium, and the following assumptions (worse case): 1) UL Time between files upload (sec) 1 and 50 Mbps; 2) DL Time between files upload (sec) 1 and 25 Mbps; 3) Time of activity 24 hrs; 5) pico cells (see table A.7 [ltu13]); 6) spectral efficiency 4 bps/Hz/cell (see Table A.12 [ltu13]). The provided bandwidth figures refer to the operational bandwidth.(*)

LAT 10 ms [Elh15]

The most critical issue is the sharing of real-time HD videos. Currently 10 ms for 2-way RAN, but typically up to 50 ms if other factors are considered (i.e., the huge number of users to be served)

UDR DL: 25 Mbps UL: 50 Mbps

The data rate in DL is already available in LTE, but it becomes critical when such huge amount of users is considered. The data rate in UL is already available in LTE but as a peak, not in average.

3.3.2 Dynamic hotspots

The main challenge of this use case is the ability to follow the traffic demand hotspots in order to allocate the computational effort only in the region where the request of network capacity is increased, and at the same time, maintaining a steady performance with all the hotspots potentially activated. The proposed solutions used in this use case are evaluated on the basis of their flexibility and reconfigurability. Within this use case, the flexibility (FVR) is the capability of a solution to work in different network conditions (e.g. indoor/outdoor, inside/outside macro layer coverage, or high/low traffic mobility). If a network has to perform in different propagation scenarios, the solution has to guarantee that:

It is capable to work with a variable number of bands deployed in the considered scenario

Coordination is supported between macro and micro layers

The reconfigurability (FVR) takes into account the time needed to switch on/off a micro layer with the goal to allocate the maximum network capacity where the highest user traffic is generated. The switch-on time is the time spent by a powered-off micro node to start the reference channel transmission, whereas the switch-off time is the time spent by a powered-on micro node from the last transmitting subframe to the power-off mode. In this use case the experienced user data rate (UDR) is a KPI used to evaluate the network performance in exploiting the activation/deactivation of micro layer to cover the data traffic hotspots. The experienced user throughput is defined as the data throughput which an end-user device achieves on the MAC layer (user plane only) averaged during a predefined measured time. Simultaneously, taking into account the experienced user throughput, an important metric is the energy efficiency of each proposed innovative solution used in the Dynamic Hotspot scenario. A description of energy efficiency (NRG) has been provided in the European FP7 project EARTH [Rub12] and it is used also within other European project like METIS [Fall13] and iJoin [Ort14]. The per bit energy efficiency is defined as the power consumed for information transmission and is represented by the equation below:



in [J/bit] or [W/bps]

In the Dynamic Hotspot use case the radio bandwidth (BW) is a KPI used to represent the amount of radio resources allocated when Micro layers are activated to offload data traffic from the hotspot. Also the radio bandwidth used on Macro layer to cover the traffic generated by the users located outside the hotspots has to be taken into account for the overall performance of the system.

Table 3-7: KPI details for the Dynamic hotspots use case


FVR < 5 minutes Time requested to adapt the system to a change of network configuration (switch on/off of one or more cells)

NRG from 40 % to 60 %

The most relevant way to reduce the power consumption is improving the way energy is spent exploiting the network re-configuration. This KPI is based on a % of the overall energy saving obtained thanks the Micro Layer efficient activation/deactivation with respect to a traditional Micro Layer being fully active.

RES 95 % (std for 5G)

Multiple RAT and Layers flexibility could be requested to maintain network access for user equipment. Although the required resilience is standard for 5G, this is not a negligible KPI as RAT flexibility is fundamental to ensure a high level of reliability.

MDV Traffic Density

DL: 750 Gbps/km² UL: 125 Gbps/km²

KPI for 5G network [Elh15] is to increase especially average and cell edge capacity in comparison to LTE Rel-12 performance.

NoU 200-2500 users/km² A 10% of activity factor per device is assumed

BW from 100 MHz to 1 GHz

(OBW)

In the dynamic hotspot the users and the network have to support the larger available transmitting band. From traditional 4G operational bandwidth (OBW) to mmWave OBW could be supported in a Dynamic Hotspot scenario

LAT 10 ms [Elh15] End to End latency is not critical in the Dynamic Hotspot use case

UDR DL: 300 Mbps UL: 50 Mbps

These values of user experience data rate have to guarantee also at the cell edge [Elh15].

3.3.3 Smart cities

Within the Flex5Gware perspective, a significant part of the focus is on 5G network enhancements related to the Smart cities use case. Accordingly, most of the proposed KPIs



have a network oriented perspective. These network KPIs measure the quality properties of the communication medium through which observed data are transferred from the measuring/acting devices to the data processing or managing servers. In addition to the network oriented perspective, Flex5Gware also addresses enhancements on 5G terminal devices. For that reason, in some KPIs, such as the one related to energy efficiency, the focus is shifted towards the IoT device. Before presenting the KPIs related to this use case, it is important to highlight that the effort presented in this section is also being considered in the standardization bodies, as for instance in ITU, where a specific working group has been created to cover IoT related requirements [Itu15].

Now, the KPIs related to the Smart cities use case are:

Energy efficiency (NRG) is an important target regarding this use case, both in terms of IoT device power consumption and on the impact on the infrastructure [CiP14]. On the node side, the idea is trying to keep the device lifetime as high as possible to delay maintenance operations as much as possible.

Number of supported users (NoU) is also key to this use case, as described in, e.g., [Idc14]. The number of IoT devices in use is expected to grow exponentially in the near future. Thus, the network is supposed to be able to handle this rising number of IoT devices together with human users inside the cities.

Integration size (ISF) of IoT devices is quite important as well regarding Smart cities use case. Devices are supposed to be smaller and smaller while enhancing their computational capabilities and reducing their energy consumption. A trade off regarding all these requirements must be achieved so as to guarantee appropriate IoT nodes.

Cost (CST) is also an inherent KPI when talking about IoT devices. They are supposed to be cheap and powerful, but the main cost achievement can be obtained from the OPEX perspective, enabling network operators to reduce the cost of deployment and re-configuration of IoT nodes obtaining higher RoI figures.

Resilience (RES) is a hot topic in the R&D world right now when talking about smart cities [CiP14]. Nodes should be able to recover from power or communication shortages without losing their data. And this must also be in concordance with the size and cost reduction.

In terms of flexibility/versatility/re-configurability (FVR), on this Smart cities use case Flex5Gware aims at reducing the time needed to reconfigure the radio connectivity based on the info being gathered by IoT devices. The reconfigurability needs on 5G driven smart cities are also considered in [Idc14].

Finally, latency (LAT) can be key to certain applications. While smart metering or environmental monitoring do not need strict latency requirements, some other applications for Smart cities such as user detection need immediate reaction, and, thus, latency must be considered.

Table 3-8: KPI details for Smart cities use case.


FVR Less than 30 s radio reconfiguration time

Ability to automatically reconfigure the radio setup depending on context info.

CST Reduction factor. 1.5x reduction.

OPEX ratio reduction obtained by the fact of having flexible nodes able to integrate new and future applications on a plug & play mode.

NGR At least 2 years for IoT devices just

How much time the devices can operate without performing maintenance operations.



sending data up to 10 times a day. Up to 1

year on more restrictive cases.

RES Power and communication backup modes.

Seamless and continuous communication of nodes (or users) to application servers on an end-to-end manner. Ability to autonomously recover from power/communication failures.

NoU 1.000 IoT devices per km2 in cities in

addition to regular users.

Ability of the network to support larger number of connected devices with respect to SotA, without losing performance in terms of QoS.

LAT Time unit. Up to 1 minute on low priority IoT applications (such

as environmental monitoring) and less than 5 seconds on high priority (i.e. people detection)

Time elapsed between an event is observed at the node side and it is reported on the server.

ISF Reduction factor. 1.5x reduction.

Reduction of the size of electronic boards and sensors so as to minimize the installation costs and visual impact of nodes deployed.

3.3.4 Performance equipment

The 5G system requirements span over a very wide range and will push boundaries for all devices active in such a system. In this use case we focus on high performance equipment, e.g. devices and gadgets showing the following characteristics related to Flex5Gware KPIs:

User data rate (UDR) (UL and/or DL): Devices should be able to use multiple bands simultaneously, without impacting the single band performance or network performance. 5G terminals shall support aggregation of data flows from different technologies and carriers. Especially global roaming capabilities without degrading performance are expected, as well as support for multiple modes of operation (TDD/FDD, full/half duplex). Support for all deployed connectivity standards will also be regarded as mandatory. Seamless transmission in between bands, modes, and RATs is baseline and should not cause interruptions nor degrade the user experience. Expected user equipment data rates are outlined to range between 50 Mbps up to 10 Gbps and beyond depending on deployment and use case [Elh15], [Ewp15].

Operational bandwidth (BW): The 3GPP standardization work for 5G will not start until 2016 which means that user equipment operational bandwidth is not set yet. However, as a first assumption +100 MHz can be assumed for performance devices supporting the highest throughput.

Latency (LAT): Performance equipment should support hybrid scenarios which combine low latency and high data rates. Today 4G use cases seldom combine latency requirements and high bit rates. When heavy number crunching occurs locally in a device and network latency is of importance, typically the data rates are relaxed. The opposite is also true, e.g. for critical sensor applications a low latency is paramount but usually the need for massive data transport is not. However, in future



cloud scenarios, hybrid solutions are expected to occur that will load-share resources between different computational platforms, including mobile equipment, putting high requirements on both real time data processing and transport. One example is online gaming, but also for relaying or ad-hoc scenarios.

As described by ITU [Tti14] the required end-to-end (e2e) latency may be as low as 1 ms in specific 5G use cases. This total latency must be shared among the acting blocks in the transmission and data processing as shown in Figure 3-1, where a illustrative example of a latency budget is shown [Ull15]. The total time for device processing could be as low as 300 µs for both receiving and transmitting.

Figure 3-1: Example latency distribution from [Ull15]

Energy (NRG) efficiency: 5G high performing devices are expected to show significant better battery life time compared to the 4G baseline today. Up to 3 days of normal operation for a smart phone is anticipated by the NGMN, and when it comes to less performing equipment, beyond 10 days will be the common duration.

Cost (CST): The device cost will not increase. In most markets the average sales price for smartphones is expected to drop significantly between 2013 and 2017, i.e. during the first five years of 4G deployment [Sta15]. Only in the North American market there will be a slight increase. Given these trends, it is unlikely that 5G will be able to increase the customer spending per device. However, as performance equipment (such as high end devices) will bring added value to the consumers in terms of technical performance and GUI experience, they will not be as cost sensitive, and thus, the price level might very well be on par with 4G high end devices today.



Figure 3-2: Predicted average smartphone sales price between 2013-2017

Number of users (NoU): If we assume all human beings will have access to a mobile device, the total number equates to 7.7 billion by 2020 [Ppw20]. Today smartphones accounts for 70% of the total mobile phone sales and is steadily increasing [Aop15]. It is thus a fair assumption to say that the total number of high end 5G devices will capture a significant part of all sold handheld devices, which in the life-span of 5G will be a magnitude of billions.

Table 3-9: KPI details for the Performance equipment use case.


CST

The same physical footprint andbill of material (BOM) comparedto 4G high performance devicestoday.

Consumer devices: Very important. Small space for custom HW. Vast part of R&D NRE will be spent on SW differentiation. Industrial equipment: Increasingly important. The consumer market will define platforms for industrial applications

NRG

A smart phone should handlemore than 3 days on battery innormal use. For less performingdevices multiple days areexpected (more than 10 days forsensors etc)

Consumer devices: Not important. Global power consumption remains as a metric for the infrastructure, not devices. Power consumption important from an end user experience perspective. Industrial equipment: Not important.

RES 99.999% availability for the most

critical use cases

Consumer devices: Application driven requirements. Industrial equipment: Potentially very high



requirements. Critical applications may have very high demands on down-time etc.

NoU Billions of users.

Consumer devices: Billions during the life span of 5G. Industrial equipment: Potentially very dense locally (production floors may have hundred connected devices), but when integrated over larger areas few compared to consumer market.

BW 100 MHz operational bandwidth

Consumer devices: Application dependent. Correlated with mobility and physical size (antenna options, power supply). Operational BW important to support peak data rates. Band selection important for coverage and mobility. Industrial equipment: BW is driven by the consumer market as consumer COTS will be deployed.

LAT 150 µs from antenna to

processed data

This KPI is associated with the network round trip time. In the most extreme scenarios the processing latency in a device must be on par with the air interface latency. Consumer devices: Most often, latency and BW do not show high requirements simultaneously. Will only happen in special scenarios, e.g. hybrid solutions with mixed computation (device and cloud) demanding both high BW and low latency. Industrial equipment: Depends on application. Very important in specific real time applications (e.g. control loops).

UDR

10 Gbps in specific scenarios

100 Mbps in urban areas 50 Mbps everywhere

Consumer devices: Application dependent. User data rate primarily important for stationary indoor scenarios or mobile compartments (plane, bus, train, car) with external capabilities. Industrial equipment: Typically, lower needs than the leisure industry (video, gaming), but specific MTC may call for higher throughput (e.g. video surveillance).

ISF Same physical footprint and BOM

cost compared to 4G high performance devices today.

Consumer devices: High integration needed to support cost structure and design aspects. Will challenge other KPIs associated with power and size. Industrial equipment: Same integration level as for consumer market, but final form factor may allow for special needs, i.e. battery size, cooling, I/O, protection etc.



3.3.5 50+ Mbps everywhere

Clearly, the most important KPI for this use case is the user data rate (UDR), which must be guaranteed at every location of the service area, even in the cell edge in remote rural areas. In particular, each user should be able to experience a data rate of at least 50 Mbps in downlink and 25 Mbps in the uplink. In some references, [Ela15][Elh15], the figure of 100 Mbps for the downlink data rate is also presented in use cases similar to Flex5Gware’s 50+ Mbps everywhere.

The remainder of the KPIs related to this use case are explained thereafter:

Mobile data volume (MDV). Based on the minimum throughput requirement of 50 Mbps together with the active user density in different areas (taken from [Itu06],[Itu12]), the mobile data volume can be computed as:

1. Far remote rural: Having the order of 10 active users per square kilometre implies a mobile data volume of, at least, 500 Mbps/km2. 2. Rural: Having the order of 100 active users per square kilometre implies a mobile data volume of, at least, 5 Gbps/km2. 3. Suburban: Having the order of 500 active users per square kilometre implies a mobile data volume of, at least, 25 Gbps/km2.

Bandwidth (BW). Recalling the expression presented in section 2.3.5, the required operational bandwidth BW that will need to be supported at the terminal side, assuming that a certain spectral efficiency ε can be achieved, is given by:

Thus, plugging the 50 Mbps rate that is to be guaranteed in the previous equation, for a given spectral efficiency, we can find the minimum operational bandwidth required to support the rate. Forecast spectral efficiencies for 2020 can be found, e.g., in [Itu13], and are reproduced in the following figure for the sake of completeness.



Figure 3-3: Forecasted spectral efficiencies in 2020 by ITU-R for RATG 1 (pre-IMT, IMT-2000 and its enhancements) and RATG 2 (IMT-Advanced)

As it can be seen from the previous figures, the spectral efficiency can take very different values depending on the exact radio environment (macro cell, micro cell, hot spot, etc.), on the type of communication (unicast or multicast) and also on the radio access technology group (RATG). Note that, as described in [Cer15], it is expected that, by 2020, both RATG 1 systems (like WCDMA or GPRS) will coexist with RATG 2 systems (e.g., LTE and LTE-A) and each system will have a strong user base.

Since we are interested in guaranteeing a minimum rate everywhere and under all circumstances, we need to take into account the minimum value of the spectral efficiency to obtain a bound on the minimum bandwidth that any 5G user terminal should fulfil in order to satisfy the requirements of the 50+ Mbps everywhere use case. In addition to that, as it is also pointed out in [Itu13], in practice, such spectrum efficiency values are unlikely to be achieved due to the random nature of traffic, errors caused by radio channel conditions or packet losses. Furthermore, simulation models show that actual spectral efficiency values are lower than the values shown in Figure 3-3.

Thus, taking a conservative estimate, a safe minimum value of the spectral efficiency that will be achieved everywhere in the cell under all circumstances is , which implies that the minimum maximum bandwidth that will need to be supported by terminal devices is MHz. Observe that this does not imply that terminal devices should always have operation bandwidths above that value. For example, in situations where the spectral efficiency can be very high (e.g., under the coverage of a hot spot), the user terminal may operate at bandwidths below 50 MHz and still be able to sustain a rate of 50 Mbps. The main implication of the above result is that terminal devices should be equipped with the capabilities to operate at bandwidths of 50 MHz or above.

Flexibility, versatility, re-configurability (FVR). In order to deal with the capacity requirements in this use case and, especially, with the anticipated heterogeneity of traffic in 5G, an increase in HW flexibility, versatility, and re-configurability is required [Ban14]. Re-configurability should be based on different context estimates (e.g., traffic type, signal quality, interference, position estimates) to modify the operation of the RAT in a timely manner, to adapt it to context variations and sudden changes in the scenario to maintain the user rate above the threshold. But, more significant in this particular use case, is the flexibility and versatility that can be provided at the base station by, e.g., multiband transmit-chains that provide a high degree of versatility with regard to the implementation for different power levels, number of antennas and, very importantly, supported radio bands to enable, e.g., multi-RAT operation.



Resilience, continuity (RES). It is clear that a significant level of reliability and continuity is required in order to ensure that the 50+ Mbps are guaranteed even in the case where the user is on the move or in the presence of rapidly changing channel conditions. One of the most important features of the SW platforms developed in Flex5Gware, is that they will have the capabilities to always select the most appropriate RAT among the plethora of possibilities offered by 5G depending on the particular scenario and propagation conditions in such a way that the service resilience and continuity is guaranteed. In particular, the selection of MIMO technology [Boc14] is of paramount importance in this use case as the use of multiple antennas can provide an efficient method to increase the signal resilience without increasing the transmission power.

Energy efficiency (NRG). The Radio Access Networks (RAN) is consuming a significant share of the overall energy consumption [Aue10]. In this particular use case, the situation could be even worse because of the requirement of 50+ Mbps everywhere. This requirement has a direct impact on the energy consumption both at network and terminal sides as it has to be met at the cell edge, which requires additional transmission power. Under the specific circumstances of this use case, in the HW domain, techniques that can improve the energy efficiency of the power amplifier (both at base stations and user terminals) such as Peak to Average Power Ratio (PAPR) reduction, pre-distortion and envelope tracking techniques can lead to improvements of up to 50 % at the base station and up to 30 % at the device level. Moreover, in the SW domain, control and management plane tools and flexible SW solutions for C-RAN environments that offer energy efficiency through coordination and dynamic reconfiguration, which are clear enablers towards an energy efficient network operation and service deployment, can offer energy savings about 25 – 30 % of the energy consumed by remote radio heads (RRH) and overall energy savings ranging from 40 to 60 % thanks to the activation/deactivation of RRH.

Table 3-10: KPI details for 50+ Mbps everywhere use case.


FVR

Capability to provide multiband operation

(e.g., 6x20 MHz channels)

Multiband transceivers can enable the operation at overall bandwidths above 1 GHz (gain factor of 10 with respect to current technologies) with a targeted frequency band of operation between 2.5 and 4.2 GHz.

NRG

Energy savings in the range of 25 - 60 % with

respect to current existing solutions

These energy savings are obtain in different domains (HW and SW) of the communication chain.

RES

Resilience is achieved via MIMO operation, with a minimum number of 8 transmitters at the base

station.

By up scaling the HW implementation of the base station transmission chain, a significantly increased number of transmission chains can be supported, enabling massive MIMO operation (e.g., beamforming or MU-MIMO techniques).

MDV

Far remote rural: 500Mbps/km2. Rural: 5 Gbps/km2. Suburban:25 Gbps/km2.

Far remote rural: ~10 users per square kilometre. Rural: ~100 users per square kilometre. Suburban: ~500 users per square kilometre.



BW ≥ 50 MHz

This KPI value is obtained assuming that, in 5G, an efficiency of around 1 bps/Hz can be achieved even at the cell edge. Also, this KPI value should be understood as the minimum maximum operational bandwidth that all terminal devices should be able to support in 5G.

UDR DL: 50 Mbps

(100 Mbps, if possible) UL: 25 Mbps

That high data rate is expected at every location of the service area, even in the cell edge in remote rural areas and with the possibility that the user is on the move.

3.3.6 Connected vehicles

We provide below the two different set of KPIs for the Connected vehicles use case, depending on the target application considered: the “broadband in vehicles” applications on the one hand (e.g., information society on the road), and the “V2X” on the other hand (for driving-specific applications).

Mobile broadband in vehicles

Vehicular communications have been historically considered not power constrained. Vehicles produce energy that is used by the infotainment/communication system just for a negligible part. Having said this, energy efficiency is advisable for the wireless technologies, and therefore energy-savings from for other scenarios may still be applied here, but it is not the main focus.

Resilience and continuity (RES) are not an issue when talking about infotainment. Being a non-critical service, service continuity could be envisioned with the same targets as other scenarios (i.e., broadband everywhere). Flexibility, Versatility, and Re-configurability (FVR), in contrast, constitutes a relevant KPI for this scenario as the vehicular scenario imposes rapidly-changing conditions due to various reasons, e.g., high speeds in highway scenarios and fast fading in urban scenarios. Because of this high dynamicity, it results critical for the card to be able to change its mode of operation as well as that this change is quick enough.

The capacity of the network (both in terms of mobile data volume (MDV) and number of users (NoU)) is the most important KPI for this use case. During traffic jams or heavy congested rush hours, vehicles are travelling at very low speed, causing peaks in both the mobile data volume and connected users comparable to other massive people gatherings. Here, the coordination between the cellular network and small cells comes into the picture. Using heterogeneous RATs with point of attachments placed in well-defined locations (i.e., intersections, traffic light posts) better connectivity (both in terms of volumes and number of users) may be achieved. This is because vehicular mobility patterns are predictable and constrained by road infrastructure. Using especially tailored mobility mechanisms, capacity may be provided just where needed and when needed, selectively offloading flows from the cellular network to the small-cell infrastructure. Going one step further, the vehicle itself may be considered as small cell. Using a dedicated base station (an 802.11 AP) that bridges UE within the vehicles to the access network outside the vehicle, higher data rates may be achieved, making also the communications started by the UEs unaware of the used mobility management schemes.



Table 3-11: KPI details for Broadband in vehicles


FVR

Capability to adapt to fast varying radio conditions, and to

activate other RATs

Due to the fast speed of mobiles inside vehicles, and the additional attenuation due to metal, the link between the terminal and the base station would suffer from high variability in some scenarios. This can be addressed via a fast adaptability to changing conditions, which could include e.g. the use of device-to-device communications to connect to another terminal with better coverage.

MDV Urban: 150 Gbps/km2.

Suburban: 50 Gbps/km2. Highway: 25 Gbps/km2.

These figures are obtained following the foreseen figures of the NoU specified above, and the target UDR from the figures below. Note that they differ from the 50+Mbps everywhere as vehicles densities are different from population densities.

NoU

Urban: 1000-3000 vehicles/km2

Suburban: 500-1000 vehicles/km2

Highway: 100-500 vehicles/km2

For each scenario, the communication range (Cell radius) is approx.: Urban (50-100 m), Suburban (100-200 m), Highway (200-1000 m). Depending on the actual deployment of the communication infrastructure, this will result in different ratios of user/antenna. Considering coverage as the limiting requirements, this ranges from 100 users/antenna in the urban scenario to 1600 users/antenna in the highway case.

UDR

Instantaneous: 50 Mbps/vehicle (DL)

Operation: 5 Mbps/vehicle (DL)

Considering that users at vehicles have less demanding requirements and that the car introduces 15-20 dB of additional attenuation, the requirements are less stringent than in the 50+Mbps everywhere, targeting a peak data rate of 50 Mbps but a sustained data rate of 5 Mbps..

V2X communications for enhanced driving

V2X communication for safety and driving assistance are probably the most relevant key use case for the wide adoption of connected vehicles. Therefore, 5G networks must meet the envisioned requirements for these applications, namely, resiliency (RES), latency (LAT) and mobile data volume (MDV).

In fact, in this case there is also a clear distinction between safety applications for vehicular networking among those using multimedia capabilities (like see-through [Fgv15]) and others that involve the fast spreading of Context Awareness Messages (ETSI TS 102 637), related to automatic or assisted driving (i.e., for intersections).

For the first family, the efficient distribution to localized targets (see-through may be useful for 5 to 10 vehicles at most) of multimedia impose the use of relatively high bandwidth technologies.



The second family, on the other hand, envisions the fast dissemination of short (a few hundreds of bytes) but very frequent (about 10 updates/second) Context Awareness Messages, including vehicle position, speed or other vehicle-related information (whether it is braking or not, the turning direction, etc.). The spreading of this information should be fast and ultra-reliable especially for vehicles close to the source, where the reaction time is reduced.

For farther vehicles, these requirements may be less strict. The Awareness information is still valuable (e.g., for vehicle platooning purposes) but the reaction times being larger, also the communication requirements may be less challenging.

Table 3-12: KPI details for V2X communications


RES

10-5 loss rate for automated operation (overtake, collision

avoidance) 10-3 for status updates

on trajectory (crossings)

To maximise delivery ratio in the wireless medium, apart from e.g. reliable multicast strategies, the use of heterogeneous technologies in parallel have to be considered, including multi-hop short range communications (for close by vehicles), broadcast using reliable coding schemes, and the use of the cellular network and road side units (RSU).

LAT

10 ms for automated operation, 50 ms for

streaming (see-through, bird’s eye view in

intersections)

The 10 ms requirement corresponds to the same application scenario as the 10-5 reliability, and therefore will be met through the use of multiple technologies. The 50 ms scenario for see-through application is less stringent, given the LoS communication and the relaxed reliability requirements.

UDR 10 Mbps for see-through, 40 Mbps forintersections.

The see-through applications do not impose strict reliability or delivery constrains, and therefore this relatively high bandwidth could be applied through efficient (but not necessarily 100% reliable) techniques.

3.4 Flex5Gware KPIs at a glance and relationship to the work in other work packages

In Section 3.3, we have defined and quantified the high level KPIs that are relevant for each use case defined in Section 2. To provide a quick summary of Section 3.3, we have created Table 3-13, which contains all the KPIs of the different Flex5Gware use cases.

The KPI summary provided in Table 3-13, will be used as a benchmark to assess the progress made by the different Flex5Gware technical work packages by the end of the project. However, it is important to highlight here that, for each one of the use cases, these KPI figures are targeting the 2020 time frame and, thus, it would be unrealistic to expect to fulfil all those KPIs by a single project from Phase I.

From all that has been said above and in the previous sections, the work carried out in WP1 during the first 6 months has served to provide a common framework for the rest of the contributions of Flex5Gware. This common framework is composed of the use cases and high level KPIs that all Flex5Gware technical contributions will refer to. An illustration of this relationship between WP1 and the rest of technical work packages in Flex5Gware is provided in Figure 3-4.

.



Table 3-13: Flex5Gware KPIs at a glance

KPI\UC CV DH SC PE 50+ MBV V2X

FVR < 30 s < 300 s < 30 sMultiband

operation

Capability to adapt to fast varying radio conditions, and to activate other RATs

CST 1.5x reduction.

Same BOM cost

compared to 4G high

performance devices

today

NRG

From 40 %

to 60 %

reduction

1‐2 years

batteries

3 days batteries

(smart phones)

More than 10 days

(less performing

devices)

From 25 %

to 60 % reduction

RES 95 % 95 %

Power and

communication

backup modes.

99.999 % MIMO operation

99.999 %

(automated

operation)

99.9 %

(status updates)

MDV

DL: 3.75

Tbps/km²

UL: 7.5

Tbps/km²

DL: 750

Gbps/km²

UL: 125

Gbps/km²

Far remote rural:

500 Mbps/km²

Rural:

5 Gbps/km²

Suburban:

25 Gbps/km²

Urban:

150 Gbps/km²

Suburban:

50 Gbps/km²

Highway:

25 Gbps/km²

NoU150000

users/km²

200‐2500

users/km²

1000 IoT

devices/km²Billions of users

Urban:

1000‐3000 veh/km²

Suburban:

500‐1000 veh/km²

Highway:

100‐500 veh/km²

BW3 GHz UL

1.5 GHz DL

from 100 MHz

to 1 GHz100 MHz (OBW) ≥ 50 MHz

LAT 10 ms 10 ms

< 60 s

(low priority)

< 5 s

(high priority)

150 µs

(from antenna to

processed data)

10 ms

(automated

operation)

50 ms (streaming )

UDRDL: 25 Mbps

UL: 50 Mbps

DL: 300 Mbps

UL: 50 Mbps

10 Gbps

(in specific scenarios)

100 Mbps

(in urban areas)

50 Mbps

(everywhere else)

DL: 50 Mbps

(100 Mbps, if

possible)

UL: 25 Mbps

Instantaneous:

50 Mbps/veh (DL)

Operation:

5 Mbps/veh (DL)

10 Mbps

(see‐through)

40 Mbps

(intersections)

ISF 1.5x reduction.

Same physical

footprint compared to

4G high performance

devices today



Figure 3-4: Graphical representation of the relation between Flex5Gware WP1 and the work carried out in WP2, WP3, WP4, WP5, WP6. The depicted arrows between use

cases, KPIs, and PoCs are just examples and are not meant to be exhaustive.



One of the most important outcomes of the Flex5Gware project will be the PoCs. Each PoC has an associated PoC ID card, where technical information related to the PoC is stored. In particular, each PoC ID card contains the description of each one of the building blocks that Figure 3-4 compose the PoC and that are developed in WP2, WP3, WP4, and WP5 (for example, in Figure 3-4, the first PoC is composed of building blocks developed in WP2 and WP3). Moreover, each PoC ID card contains the Flex5Gware use cases and high level KPIs that are relevant to that PoC. In addition to that, each PoC ID card contains a Test Object List (TOL) that describes a set of low-level KPIs (LLKPI) that are specifically related to HW/SW platforms and that are the quantities that will be measured from each PoC.

Thus, the link between Flex5Gware contributions to the impact on high level 5G-PPP KPIs is established: Flex5Gware contributions PoC low-level KPI Flex5Gware KPIs 5G-PPP KPIs.

Although, the complete PoC ID card will be available by M12 in D6.1, the internal report IR6.1 has been ready from M6 and it contains the draft/preliminary version of the PoC ID cards. Nonetheless, for the sake of completeness, in the following section, a brief description of the Flex5Gware PoCs is provided together with the links with each use case.

4. PoC and Use Case Mapping A Proof of Concept (PoC) is a SW and HW platform used to demonstrate technologies and services; in particular, in F5GW the PoCs refer to the 5G world. The PoCs listed in this section can provide a demonstration of a single 5G technology or multiple 5G technologies in order to contribute to the main activities of the project.

4.1 PoC overview

The PoC mainly involve the principal 5G functionalities like: efficient HW/SW operation, reconfigurable HW and HW agnostic SW, HW solution for high frequency communication allowing a Full Duplex transmission in the same time on the same frequency and new solutions for power consumption reduction. Each PoC, that involves a single or multiple of the above mentioned technologies, is linked to one or more of the use-cases described in Section 2.3 that summarizes the most common applications of the 5G targeted scenarios. The PoC and use-case association is show in the table below:

Table 4-1: Association of the PoCs with use cases in Flex5Gware

Use Case PoC

Cro

wde

d ve

nues

On chip frequency generation (PoC 1) Multiband Transmitter (PoC 4) Full Duplex FBMC transceiver (PoC 5) High-speed low power resilient LDPC decoder (PoC 6) Multi-chain MIMO Transmitter (PoC 11)



Dyn

amic

Hot

spot

On chip frequency generation (PoC 1) Multiband Transmitter (PoC 4) Full duplex FBMC transceiver (PoC 5) High-speed low power resilient LDPC decoder (PoC 6) HW/SW function split for energy aware communications (PoC 7) Reconfigurable programmable radio platform (terminal side) and

SW programming performed and injected by the network (PoC 8) Flexible, scalable and reconfigurable small cell platform (PoC 9) Flexible resource allocation in CRAN / vRAN platform (PoC 10) Multi-chain MIMO Transmitter (PoC 11)

Sm

art

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Active SIW antenna systems for the 20-40 GHz band (PoC 2) PAPR reduction and power amplifier pre-distortion (PoC 3) Reconfigurable programmable radio platform (terminal side) and

SW programming performed and injected by the network (PoC 8)

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50+

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PAPR reduction and power amplifier pre-distortion (PoC 3) Multiband Transmitter (PoC 4) Flexible, scalable and reconfigurable small cell platform (PoC 9) Flexible resource allocation in CRAN / vRAN platform (PoC 10) Multi-chain MIMO Transmitter (PoC 11)

Mob

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HW/SW function split for energy aware communications (PoC 7) Reconfigurable programmable radio platform (terminal side) and


For each PoC, the following sections describe how they address the selected use cases and KPI targets. 4.1.1 On chip frequency generation

This PoC addresses the need to generate low cost, small footprint fully integrated frequency synthesizers. The work will cover the full frequency generation system, including transport of signals to receiving blocks, e.g. up and down conversion mixers. As a first step, frequencies up to 30 GHz will be studied, but extended to also include 60 GHz scenarios as part of the



cooperation with Lund University. Key aspects in the study will comprise performance parameters like power consumption, phase noise etc, but also production aspects like low cost technology options and co-integration in monolithic radio SoCs where signal integrity is important. For a 5G system to become attractive on the broader market, including IoT, device cost and power consumption has to be kept low as well. The goal for this PoC is thus to improve these parameters compared to state of the art.

Figure 4-1: The PLL architecture (a) and its use in a receiver architecture (b).

Although the usage of high performing, cost efficient clock and frequency generation is paramount for many of the outlined use cases, special focus will be on the use case families Massive internet of things and Broadband access in dense areas as these two together combine the urge for cost efficient high frequency (mmWave) hardware. In particular, the cost efficiency is especially relevant in the Massive internet of things use case family as it requires the deployment of a very high number of devices, and the operation at mmWave is a key feature that will be required to achieve the very high date rates expected in the Broadband access in dense areas use case family. 4.1.2 Active SIW antenna systems for the 20-40 GHz band

The PoC focuses on the development of an integrated antenna and power amplifier system operating in the 20 GHz – 40 GHz band. Power amplifiers are critical components of the RF front-end of 5G wireless systems as they are responsible for providing the required transmission signal power and consequently they consume a large portion of the system power. At the same time, the antenna is typically a circuit component which requires a large area and careful design in order to minimize unwanted radiation interference and optimize coverage. Although most electronic components have continuously decreased in size, the antenna dimensions must remain in the order of the wavelength to ensure good radiation efficiency. The use of higher operating frequencies such as the considered 20 GHz – 40 GHz band permits a larger bandwidth and smaller antenna size. Integrating these two components represents a challenge in order to minimize cost and power losses, maximize energy efficiency and eliminate unwanted spurious transmissions. This PoC explores two different power amplifier design options, one based on an integrated (IC) solution and one based on commercial-off-the-shelf components as alternatives to produce cost effective yet high performance solutions. At the same time the PoC places emphasis in the co-design of



the amplifier with the antenna and their interconnection, in order to both minimize dissipation losses and interface properly the two circuits for maximum energy efficiency. The full-wave/circuit co-design of this active antenna will demonstrate the benefits in terms of bandwidth and energy efficiency compared to a simple concatenation of a stand-alone antenna and a stand-alone power amplifier. These new active transmit antennas with integrated power amplifier are well-suited to the 5G use case requirements for RF frontends. Specifically, under the Massive internet of things use case family, the deployment of large numbers of wireless devices that provide communication, sensing and/or localization functionality is required. To properly meet the requirements of this use case family, the communicating devices must satisfy a set of constraints: a) they need to be low-cost in order to facilitate their commercial deployment, b) they need to be easily integrated in their environment setting for aesthetical reasons, c) they need to be energy efficient, autonomous and even recyclable for practical and ecological reasons. This PoC represents an important step towards the successful commercialization of 5G wireless systems by leveraging the co-design of two critical analog components such as the power amplifier and the antenna, with an aim to fulfill the above constraints and especially towards cost effective solutions which are additionally, low profile, energy efficient and unobtrusively integrated with the environment. Thus, from all that has been said above, the contribution in this PoC is relevant for all the use cases under the Massive internet of things use case family: Smart cities (low cost, environment integration), Performance equipment (mmWave operation and high bandwidth, user rate), and V2X communications (enhanced user data rate thanks to the operation at mmWave). 4.1.3 PAPR reduction and power amplifier pre-distortion

The 4G system adopts OFDMA technique and faces several limitations: high frequency/phase noise, spectrum shaping problem, a long symbol duration and high peak-to-average power ratio (PAPR). In 5G systems, we need to solve those problems and meet 5G requirements such as support for fragmented spectrum, suitability for short bursts, robustness to frequency/timing offset, low cost, and low latency. The OFDMA technique is still an important candidate for 5G system. In addition, several candidate waveforms are investigated such as Filter-Bank Multi-Carrier (FBMC), Non-orthogonal asynchronous waveforms, Generalized Frequency Division Multiplexing, and Universal Filtered Multi-carrier. These waveforms are based on multi-carrier technique and suffer from high PAPR. The high PAPR causes signal distortion and high energy consumption. It is essential that a transmitter has a power amplifier which provides a suitable power for transmission. The power amplifier is very sensitive to operational area which requires a linear area. The high PAPR causes a nonlinear operation problem and this problem causes a signal distortion. In addition, the PAPR is highly related to power amplifier efficiency as follows:

= 0.5/PAPR where denotes the power amplifier efficiency. Digital Pre-distortion (DPD) techniques are used to compensate for the non-linear behaviour of the power amplifier. They apply inverse distortion to the input signal of the power amplifier in order to compensate the distortion generated by the power amplifier. The DPD technique must typically be applied at a sample rate reaching at least 3 or 5 times the baseband signal bandwidth. In 5G systems, we anticipate ultra-wide bandwidth due to very high data rate. Thus, one of the key research challenges is to develop a high speed DPD algorithm. In PoC 3, feasibility and performance of PAPR reduction as well as pre-distortion for 5G power amplifier (PA) will be studied by measurements. The expected benefits are as follows:



- Energy efficiency improvement by a new PAPR reduction technique and DPD technique.

- Cost reduction due to a low operational cost and longer battery life.

Achieving an energy efficiency improvement in the power amplifier is critical in situations where a certain performance requirement is expected at the cell edge, which is the location where more power is needed to sustain the quality of the communication. Thus, this PoC is especially relevant in the 50+ Mbps everywhere use case, where this stringent requirement for the user data rate must be guaranteed everywhere and, in particular, at the cell edge. Moreover, since the developments carried out within this PoC will yield a significantly longer battery life and cost reduction, it is also meaningful in the two use cases within the Massive internet of things family (Smart cities and Performance equipment) such that energy and cost constraints are placed on the device terminals. We have not considered that this PoC is relevant in the third use case in the Massive internet of things family, “V2X communications for enhanced driving”, because, e.g., battery life is not a pronounced issue in vehicular communications. 4.1.4 Multiband transmitter

In order to provide key building blocks of versatile base stations, supporting high bandwidth of multiband transceivers, a multiband transmit-chain is considered for a frequency range between 2.5 and 4.2 GHz at power levels suitable for medium or large inter-site distances. The concept of multiband transmitters provides an increase of operation bandwidth of aggregated carriers enabled by the concurrent transmission of multiple carriers (e.g. up to 6 x 20 MHz) allocated to multiple radio bands. An increase of the radio bandwidth is obtained be the potential operation at different frequencies within the addressed bands between 2.5 and 4.2 GHz by supporting up to three radio bands. The increase of operation bandwidth supports increasing the mobile data volume provided by the base station. The concept of the multiband transmit-chain shows a high degree of versatility as it can be applied for different frequency ranges below 6 GHz. It supports multi-RAT operation, including new wave forms expected for 5G wireless systems. By combining such transmit-chains for different frequency ranges in a modular way, a base station of further increased operation and radio bandwidth can be realized with the corresponding increase of cell capacity. It shows certain flexibility due to the frequency agility, which allows moving the frequencies of operated carriers within the radio bands and between them by re-configuring the transceiver, while the degree of flexibility is defined by the complexity of implementation. As a concept for hardware solutions for versatile bases stations, the multiband transmit-chain that will be developed for this PoC shows a significant degree of universality with regard to the implementation for different power levels, number of antennas or supported radio bands. Accordingly, it enables an increase of mobile data volume thanks to the increased bandwidth combined with the versatility provided by the multiband operation. Thus, this PoC supports all use cases that are related to use case families that involve broadband access: Broadband access in dense areas and Broadband access everywhere. In particular, the four use cases within these two families are: Crowded venues, Dynamic hotspots, 50+ Mbps everywhere, and Mobile broadband in Vehicles. 4.1.5 Full duplex FBMC transceiver

The goal of this PoC is to demonstrate the practical feasibility of a full duplex transceiver combined with a new waveform foreseen in 5G: filterbank multicarrier modulation or FBMC. The major challenge of a full duplex device is the suppression of the self-interference. Since the power difference between the receiver signal and the interfering transmitter signal could exceed 80 dB, it is impossible to cancel the whole interference after the A/D conversion.

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The reconfiguration of the HW‐SW baseband functions of the small cell nodes has as a goal to reduce their energy footprint. The instantaneous capacity and latency requirements (BW, multi‐antenna scheme, number of

subscribers etc) define the reconfiguration scenario, presuming that the traffic data is known a priori.

Figure 4-4: A high-level overview of the proposed architecture

Accordingly, the goal of the reconfiguration would be to show energy savings at the eNB level. Hence, the energy cost of the different network configurations modes will be measured and, on top of it, a series of run-time modifications at the PHY-layer can also be applied; for instance tuning parameters such as the signal bandwidth, the channel coding, the multi-antenna scheme or even switching from a 4G waveform to a 5G one. The energy measurements at the eNB will include the baseband processing chip, the RF transceiver, the power amplifier (PA) and the high speed communication links (e.g., CPRI, 10GE). Thus, the energy savings benefits when applying one of the three network reconfiguration modes will be quantified. From everything that has been said above, it is clear that two of the most important KPIs in this PoC are flexibility, versatility, re-configurability (FVR) and energy efficiency (NRG) and it deals with situation where the overall capacity requirements cannot be sufficiently served by the macro base stations is especially well suited for the Dynamic hotspots use case. However, the specifics of vehicular communications (high variability of the channel due to vehicle speeds) can also be appropriately dealt with by the features of this PoC thanks to its re-configuration capabilities, which enable it to, e.g., guarantee a certain resilience level even under changing channel conditions. Thus, this PoC is also relevant in the two use cases related to vehicular communications: Mobile broadband in vehicles and V2X communications for enhanced driving.

4.1.8 Reconfigurable programmable radio platform (terminal side) and SW programming performed and injected by the network

The goal of this PoC is demonstrating the whole adaptation loop of 5G technologies, by reconfiguring the radio behaviour according to advanced context estimates (e.g., provided by sensors) and different optimization criteria. The main idea is abstracting the wireless device resources regardless of the specific internal architecture, by exposing simple programming interfaces able to read the state of the resources and to enforce a desired configuration,



according to decisions taken by a local SW agent interacting with a remote network controller.

To achieve this aim, in this PoC, we define novel radio platform architecture based on an agile radio terminal, which is programmable both in PHY and MAC levels with a cross-layer approach. We want to satisfy the flexibility/(re)configurability KPIs by increasing the terminal programmability, adopting the abstraction architecture given by the Wireless MAC Processor (WMP). Thanks to WMP approach, we want to extend it with more physical oriented primitives obtaining a PHY/MAC API that allows us to design radio program and inject it into terminal allowing, for example, to work in non-standard sub-carriers or to fit with variable bandwidth size allocation. Flexible terminal can be programmed on the fly using several coordination strategies that can be oriented in a centralized or decentralized way. For example, we design a local control logic that can trigger the most appropriate radio program to optimize the channel usage, thus increasing the performance. On the other hand, WMP nodes that interact with a centralized controller can be used to program radio terminals, in this way a global coordinator is able to assign an optimized radio program to each node. Cross-technology coexistence can be achieved by the introduction of novel techniques of PHY measurements, used as input to MAC controllers, which define a smart spectrum allocation for the node improving performance and medium allocation. We are exploiting existing programmable radio board based on FPGA, which works on unlicensed frequencies and give a programming framework, which however does not allow in principle any dynamic reconfiguration in runtime. We just introduce WMP implementation in this platform and we are working to extend the API set to introduce enhanced event, condition and actions, which works directly with PHY primitives.

Figure 4-5: (1) WARP 802.11 architecture vs. (2) WMP WARP architecture

In Figure 4-5, the layer block architecture of our solution is shown. The MAC protocol layer is programmed in the Microblaze CPU and we just extend the standard functionalities by the definition of a Finite State machine engine which is fully programmable in runtime by the injection of a user-defined state machine. The FPGA core contains the physical functionalities and the target is to define a programming logic to also allow for runtime reconfigurability, i.e. defining a so-called “configuration chain” for transmitter and receiver modules. Moreover a deeper knowledge of the PHY levels defining more physical metrics that can be useful for medium access logic, which is able to avoid interference or optimize the data delivery. Solutions to avoid channel interference on MAC layer will be studied, e.g. defining pattern recognition for an interferer combined with a TDMA access scheme (Figure 4-6 (2)). Our experiments want to show how an environment with flexible nodes permits to avoid collisions interacting with other resource-consuming technologies such as LTE or ZigBee.



Figure 4-6: ISM coexistence (1) scenario, (2) TDMA approach, (3) frequency-bandwidth allocation

The relation of this PoC with the Flex5Gware use cases is very similar to that of the previous PoC because, both PoCs share flexibility, versatility and re-configurability (FVR) as one of their main features. Consequently, this PoC is meaningful in the same use cases as the one in the previous section: Dynamic hotspots, Mobile broadband in vehicles and V2X communications for enhanced driving. However, given that this PoC is able to reconfigure the radio behaviour according to advanced context estimates, which are mainly provided by sensors, it can also be relevant under the Smart cities use case as this is the natural environment where context information is more readily available.

4.1.9 Flexible, scalable and reconfigurable small cell platform The goal of the PoC is developing a SW-based, low-energy, low-cost, virtualized small cell platform. The proposed solution would allow the small cell's owner to not only deploy network processing right at the edge, but also to sell access to the equipment to third-parties (like independent tenants that share the same platform). The virtualized SW based smalls cell can enable: the process offloading in order to save mobile device battery, new low-delay services (e.g., augmented reality, local mixing servers for IP-based conferencing), edge-based data analytics, and context-aware services (e.g., based on the physical location of the user). According to what it’s written above, this PoC is relevant to the two use cases where the presence of small cells is of paramount importance: Dynamic hotspots (small cells can enable the micro layer, which is used to increase the network capacity in a small area where the number of users demanding high data rate can be high) and 50+ Mbps everywhere (where low-energy and low-cost small cells seem to be one possible solution to guarantee the 50+ Mbps minimum throughput in future urban environments). The general idea of this PoC is illustrated in Figure 4-7 where an Ettus Research USRP N210 software radio is connected via a 1 Gbps Ethernet cable to a commodity hardware host (a x86 server). Data are transmitted from the USRP N210 to the host over UDP. In addition,

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The PoC is used to reproduce a dense urban scenario with dynamic traffic hotspots generation. Because of that this PoC will evaluate:

the throughput gains obtained by dynamically coordinating the transmission of several RRH in the environment;

the power saving achievable with the dynamic RRH activation/deactivation and BBU allocation; this saving is also evaluated in terms of computation resources of the above coordination algorithm and how this value scales with the number of coordinated RRH;

the latency/reaction times to reconfigure the system. The main achievement of this PoC is to perform a dynamic network reconfiguration on the basis of traffic information and number of UEs; this is an important feature for Virtualized RAN application in a Dynamic hotspot use-case. The capability of minimizing the network resource utilization reconfiguring the network on user request basis can help in reducing the energy consumption and the interference, potentially by increasing also the minimum user throughput. However, in addition to its relevance to the Dynamic hotspots use case, this PoC is also relevant to the 50+ Mbps everywhere use case because the CRAN/vRAN heterogeneous network architecture dealt with in this PoC is, together with small cell deployment, a strong candidate solution to the problem of reaching 50+ Mbps everywhere. As it has been pointed out above, this kind of distributed architecture allows to implement resource allocation algorithms that can be aimed at guaranteeing a certain minimum rate for all the users. 4.1.11 Multi-chain MIMO transmitter

For supporting the operation of MIMO solutions, in this PoC, a multi-chain massive MIMO transmitter is considered for the generation of multiple (e.g. 8) RF signals in one digital device. The signal carrier of ≥ 5 MHz bandwidth is placed between 3.4 and 3.8 GHz covering the LTE frequency bands 42 and 43. The solution allows improvements in integration and size and leads to increasing the energy efficiency due to the reduced number of components. When integrating several multi-chain components in a base station transceiver the number of transceiver chains can be significantly increased, supporting massive MIMO implementation, which enables to increase the mobile data volume and the number of supported users significantly together with enabling a more cost and energy efficient usage. Accordingly, the multi-chain MIMO transmitter PoC supports the following use cases: Crowded venues (thanks to the increase of number of supported users provided by the MIMO spatial multiplexing), Dynamic hotspots (thanks to the increase of mobile data volume related to the MIMO operation and the corresponding energy efficient operation), and 50+ Mbps everywhere (thanks to the increase in achievable spectral efficiency by means of MIMO operation).



5. Conclusions In order to find tangible use cases for Flex5Gware to target, WP1 has selected a reverse engineering approach where the outlined 11 PoCs have acted as the starting point. In the process of defining relevant KPIs for the POCs, the use case definition has been worked on in parallel, where the mapping to prior art (e.g. [Oss14], [Elh15]) definitions has been emphasized. By taking this approach WP1 has simultaneously achieved a requirement break-down needed for the implementation oriented research, and anchored the PoCs to the use case family structure used among all 5G-PPP projects [EUC13].

In total three use case families have been identified, which combined, capture fundamental aspects of the 5G system. These are described in section 2.2. For each use case family, use cases have been selected as a means to validate the 11 PoCs within a context of 5G. They are described in section 2.3.

The work summarized in D1.1 will be used and further elaborated on in the other Flex5Gware studies and deliverables, as D1.1 sets the direction and targets of the project. Each outlined aspect will be particularized and investigated to illustrate implementation challenges in both the HW and SW domains, including the interaction in between. Potential solutions to reach the overall targets will by the end of the project be benchmarked against D1.1 KPIs and the outcome provided in D1.2.



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