imt-2020 evaluation: calibration of sls -...

IMT-2020 Evaluation: Calibra-tion of NOMOR’s System LevelSimulatorNovember 19, 2018Lang Yu, Christiane Dietrich, Volker PauliNOMOR Research GmbH, Munich, Germany

Summary

ITU-R is committed to deliver a specifica-tion for an international mobile telecom-munication system for 2020 and beyond(IMT-2020). ITU-R has asked for pro-posals for Radio Interface Technologies(RITs). Each submission has to includeeither an initial self evaluation or the pro-ponents’ endorsement of an initial evalu-ation according to the ITU-R guidelines.Currently, work is being performed on theIMT-2020 evaluation process. 3GPP as aproponent is performing a self evaluation.Nine organizations have indicated their in-tention to serve as independent evaluationgroups to corroborate the self-evaluationresults provided by the propoents. Oneof these was launched under the um-brella of the 5G Infrastructure Associa-tion (5G-IA), which colaborates with theEuropean Commission in the context ofthe 5G-PPP sub-program of Horizon 2020

on 5G. Within this IMT-2020 EvaluationGroup of 5G-IA, Nomor Research is re-sponsible for conducting a major share ofthe required system level simulations. Inthis document, we introduce the consid-ered scenarios including the main config-uration settings. Our considerations arelimited to the enhanced mobile broadband(eMBB) usage scenario. In the contextof self evaluation, 3GPP is performing acalibration of system level simulators ofdifferent members considering DownlinkCoupling Gain and Downlink Geometry ascalibration metrics. We performed thecalibration of our system level simulatoragainst these results and observed thatour results are well aligned.

I Introduction

In 2012, ITU-R started to develop a vi-sion of the international mobile telecom-munication system for 2020 and beyond

Nomor Research GmbH / [email protected] / www.nomor.de / T +49 89 9789 8000 1/13

referred to as IMT-2020 [IRb]. To de-termine the international specification for5G, which shall be presented in 2020,ITU-R has defined technical performancerequirements in ITU-R M.2410-0 [IR17a]and service and spectrum aspect require-ments have been summarized in ITU-RM.2411-0 [IR17b]. Furthermore, theITU-R has specified evaluation guidelinesin ITU-R M.2412-0 [IR17c] to evaluatethe candidate IMT-2020 radio interfacetechnologies (RITs) or Set of RITs (SRIT)for different test environments.

Based on the schedule presented by ITU-R WP5D, proposals for IMT-2020 canbe submitted from October 2017 to July2019. The ongoing evaluation of the can-didates will end in February 2020 [IRa].

3GPP defined a work plan for its submis-sions according to this timetable. At thebeginning of this year, the initial descrip-tion was submitted [SA18a]. It includestwo submissions: Submission 1 is an SRITcomposed by two RITs, namely New Ra-dio (NR) and LTE, where NR is the term3GPP used for the standard specified fromRelease 15 onwards. Submission 2 is anNR RIT. An update, which contains thepreliminary self-evaluation and link bud-get results and compliance templates in

addition to the extended characteristics,was submitted in October 2018 [SA18b].The final submission is planned for July2019 [Ita17]. This will include further Re-lease 16 enhancements.

ITU-R has registered nine different Inde-pendent Evaluation Groups (IEG) [IRa],commissioned to verify the performance ofcandidate proposals for 5G. Proponents,such as 3GPP, are required to perform selfevaluation based on scenarios and con-straints defined by the ITU-R in [IR17c].

The 5G Infrastructure Public Private Part-nership (5G-PPP), a sub-program of theHorizon 2020 program addressed by theEuropean Commission and the Europeaninformation and communication technol-ogy industry, organized in the 5G In-frastructure Association (5G-IA) therebyrepresenting the private side of 5G-PPP,has formed one of these registered IEGto evaluate 3GPP’s proposal based onthe IMT-2020 evaluation guidelines. Thisevaluation group mainly includes mem-bers of the EU funded Horizon 2020phase-2 projects 5G-XCast, 5G-MoNArch,One5G and 5G-Essence. Nomor Researchis part of it and responsible for many ofthe system-level simulations, specificallythose related to enhanced mobile broad-


band (eMBB).

Recently, we participated the 3GPP Work-shop on 5G NR IMT2020 evaluation inBrussels, Belgium. The workshop intro-duced the IEGs and the industry to the 5Gmobile communication system developedby 3GPP. Additionally, the 3GPP submis-sions for IMT-2020 including the corre-sponding evaluations were explained anda short outlook was presented.

The first step of the evaluation processis to calibrate the system level simulatorin simplified reference scenarios. Chap-ter II of this document introduces theconsidered scenarios and the main cal-ibration parameters including the con-figuration settings and calibration met-rics. The calibration results of Nomor Re-search’s system level simulator are com-pared against the 3GPP results in Chap-ter III. Chapter IV concludes with a sum-mary of the observations and gives an out-look regarding the next steps.

II Scenarios and CalibrationParameters

3GPP’s calibration scenarios are largelybased on the test environments defined

by ITU-R in [IR17c]. [IR17c] also spec-ifies channel models, one of which in turncoincides with that defined by 3GPP in[3GP17].

II.A Test Environments

For the IMT-2020 evaluation, the ITU-Rdefined different usage scenarios [IR17c],namely enhanced mobile broadband(eMBB), massive machine type commu-nications (mMTC) and ultra-reliable andlow latency communications (URLLC),and combines each of them with one orseveral geographic environment(s) result-ing in five different test environments,see Table 1. These give the possibility toinvestigate the critical aspects in systemdesign and performance.

Scenario Test Environment

Indoor Hotspot – eMBBeMBB Dense Urban – eMBB

Rural – eMBBmMTC Urban Macro – mMTCURLLC Urban Macro – URLLC

Table 1: Test environments defined by ITU

In this document we restrict ourselves tothe three test environments related to theeMBB usage scenario.


Figure 1: Layout for Indoor Hotspot –eMBB [IR17c]

II.B Network Layout

For the network layout no specific topo-graphy is taken into account, instead basestations are placed in regular grids [IR17c].

For the Indoor Hotspot – eMBB test en-vironment, 12 sites are placed at a heightof 3 m and with an inter-site distance of20 m in a confined and isolated area of120m× 50m, see Figure 1. The scenariorepresents one floor of a building whichhas a height of 3 m with ceiling mountedbase stations. Internal walls are modeledvia the stochastic LOS probability model.In two variants of this scenario one sitecan be configured with one or three sec-tors or cells, respectively.

The Dense Urban – eMBB test envi-ronment consists of a macro and a mi-cro layer. For the macro layer, a regu-

Figure 2: Hexagonal site layout for DenseUrban – eMBB and Rural – eMBB [IR17c]

lar hexagonal layout is used, where eachsite has three sectors, see Figure 2. Ineach macro cell area three micro sitesare randomly dropped for the micro layer.For the purpose of calibration, 3GPP andtherefore also we herein only consider themacro layer.

For the Rural – eMBB test environmentthe network deployment is the same as themacro layer of the Dense Urban – eMBBtest environment, but differs in terms ofinter-site distance and height of the basestations.


II.C Parameter Settings

In Table 5 of [IR17c] the ITU-R definesevaluation configurations for each test en-vironment. For several parameters as thenumber of antenna elements or the band-width, a range is given. 3GPP specifiedthese parameters for its calibration withinthe framework of the self evaluation. Anoverview of all parameters used is givenin e. g. [Hua18]. We applied these 3GPPparameter settings for our calibration.

For each test environment different con-figurations are available. The consideredscenarios with the characterizing configu-rations are summarized in Table 2.

Considering Indoor Hotspot – eMBBand Dense Urban – eMBB, carrier fre-quencies fc of 4 GHz and 30 GHz areused. Meaning two different frequencyranges are investigated, namely frequencyrange 1, i. e. frequencies below or equal6 GHz and frequency range 2, i. e. frequen-cies above 6 GHz. For the Rural – eMBBscenario, there are two configurations infrequency range 1, one with 700 MHz andone with 4 GHz carrier frequency.

In case of Indoor Hotspot – eMBB Con-fig A, 32 antenna elements are configuredat the base station and 4 antenna ele-

Indoor Hotspot – eMBBConfig A Config B

fc 4 GHz 30 GHzTx × Rx 32× 4 64× 32

GoB –√

Dense Urban – eMBBConfig A Config B

fc 4 GHz 30 GHzTx × Rx 128× 4 256× 32

GoB√

Rural – eMBBConfig A Config B

fc 700 MHz 4 GHzTx × Rx 64× 2 128× 4

GoB fixed downtilt

Table 2: Scenario Parameters

ments at the UE. All antenna elements arecontrolled individually meaning we have aone-to-one mapping between transceiverunits (TXRUs) and antenna elements.

We performed the calibration of all IndoorHotspot – eMBB scenarios with one sec-tor per site as well as with three sectors.As mentioned in Section II.B the configu-ration can be selected by the proponent.

A grid of beam (GoB) with 8 or 12 dif-ferent directions is applied at the gNBin the Indoor Hotspot – eMBB Config B


scenario or in the two Dense Urban –eMBB scenarios, respectively, i. e. the an-tenna elements are grouped as disjointsets into sub-array partitions served by dif-ferent TXRUs. Within the TXRUs analogbeamforming is applied on the individualantenna elements, while for the combina-tion of the different TXRUs digital pre-coding is used. In the Indoor Hotspot– eMBB Config B scenario the 64 an-tenna elements are grouped into 8 par-titions each connected to an TXRU. Eachpartition has 4 columns and 2 rows ofantenna elements. The TXRUs of thetwo Dense Urban – eMBB scenarios eachfeed partitions of 32 antenna elements ar-ranged in 8 columns and 4 rows. Whilefor Config A 4 TXRUs are used, Config Buses 8 TXRUs.

At the UE 4 antenna elements with a one-to-one mapping are configured for Con-fig A both of Indoor Hotspot – eMBB andDense Urban – eMBB. Considering theappropriate configurations of frequencyrange 2, GoB with 8 different directionsis applied at the UE. 32 antenna elementsare grouped into 4 partitions. Each parti-tion has 4 columns and 2 rows of antennaelements. While for the gNB, the TXRUsor antenna elements are positioned suchthat the beams or patterns look all into

the same direction, the partitions of thelatter configurations are as separate pan-els positioned back-to-back to allow a re-ception of all different directions.

For Rural – eMBB we have a fixed down-tilt at the base station for all TXRUs.8 antenna elements spaced in one col-umn are fed by one TXRU. For Config A(fc = 700MHz) there are 8 TXRUs, forConfig B (fc = 4GHz) 16 TXRUs, result-ing in a total number of antenna elementsof 64 or 128, respectively. On the UE side,2 antenna elements are used for Config A,whereas 4 antenna elements are used forConfig B.

At the gNB cross polarization with an ori-entation of +45 ◦ and -45 ◦ is applied. Theorientation of the antenna elements at theUE is 0 ◦ and +90 ◦.

For all simulations we apply a band-width of 10 MHz and IMT channelmodel B [IR17c] which corresponds tothe 3GPP channel model for frequen-cies from 0.5 GHz to 100 GHz specified inTR 38.901 [3GP17].

Further parameter settings can be foundin [Hua18].


II.D Metrics for Calibration

3GPP’s calibration process is based ontwo metrics, namely Dowlink CouplingGain and Downlink Geometry.

The Dowlink Coupling Gain includespathloss, antenna gains and average fastfading gains. Any processing gains attransmitter or receiver like beamformingor maximum ratio combining gain are ex-cluded, except for analog beamforminggains of the TXRUs where applicable.

The Downlink Geometry is the ratio of re-ceived signal power to the sum of interfer-ence and noise power where all signals areaveraged individually over the used band-width. Like the Downlink Coupling Gain,it does not include any processing gain attransmitter or receiver except with analogbeamforming where applicable. As suchthe Downlink Geometry is a kind of wide-band SINR.

III Calibration Results

We calibrated our system-level simula-tor against the various simulators usedin 3GPP, cf. [Hua18]. The calibrationresults, regarding the metrics DownlinkCoupling Gain and Downlink Geometry,

are presented in Figure 3 to 18. The re-sults of the various 3GPP simulators areincluded in the figures tagged with legendentries “3GPP #i”, the index i being thatspecfied in [Hua18].

The figures show a very good match of ourresults with the 3GPP results regardingDownlink Coupling Gain as well as Down-link Geometry. Only in Rural – eMBB,Config A (fc = 700MHz) our results in-dicate a slightly increased probability ofthe Downlink Geometry in the range be-low -3 dB, cf. Figure 16.

IV Conclusions

In this paper, the IMT-2020 evaluationprocess was shortly introduced and con-sidered scenarios, the main calibration pa-rameters and configuration settings areexplained. As a member of the 5G-IAindependent evaluation group responsiblefor the system level simulation, we pre-sented our calibration results against theones provided by 3GPP. We concludedthat our results match very well with the3GPP results.

In the next step we will perform the ac-tual performance evaluation following themethodology of [IR17c].


−90 −80 −70 −60 −50 −400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Coupling Gain [dB]

CD

F−

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 3: Coupling Gain, Indoor Hotspot –eMBB, Config A, 1 sector

−10 −5 0 5 10 15 20 25 300

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Geometry [dB]

CD

F −

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 4: Geometry, Indoor Hotspot –eMBB, Config A, 1 sector

−80 −75 −70 −65 −60 −55 −50 −45 −400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Coupling Gain [dB]

CD

F −

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 5: Coupling Gain, Indoor Hotspot –eMBB, Config A, 3 sectors

−10 −5 0 5 10 15 200

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Geomentry [dB]

CD

F −

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 6: Geometry, Indoor Hotspot –eMBB, Config A, 3 sectors


−100 −90 −80 −70 −60 −50 −400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Coupling Gain [dB]

CD

F−

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 7: Coupling Gain, Indoor Hotspot –eMBB, Config B, 1 sector

−20 0 20 40 60 800

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Geometry [dB]

CD

F−

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 8: Geometry, Indoor Hotspot –eMBB, Config B, 1 sector

−100 −90 −80 −70 −60 −50 −400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Coupling Gain [dB]

CD

F−

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

Nomor

Figure 9: Coupling Gain, Indoor Hotspot –eMBB, Config B, 3 sectors

−10 0 10 20 30 400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Geometry [dB]

CD

F−

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

Nomor

Figure 10: Geometry, Indoor Hotspot –eMBB, Config B, 3 sectors


−140 −120 −100 −80 −60 −400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Coupling Gain [dB]

CD

F −

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 11: Coupling Gain, Dense Urban –eMBB, Config A

−20 −10 0 10 20 30 40 50 600

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Geometry [dB]

CD

F −

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 12: Geometry, Dense Urban – eMBB,Config A

−180 −160 −140 −120 −100 −80 −60 −400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Coupling Gain [dB]

CD

F−

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 13: Coupling Gain, Dense Urban –eMBB, Config B

−40 −20 0 20 40 600

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Geometry [dB]

CD

F−

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 14: Geometry, Dense Urban – eMBB,Config B


−160 −140 −120 −100 −80 −60 −400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Coupling Gain [dB]

CD

F −

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 15: Coupling Gain, Rural – eMBB,Config A

−20 −10 0 10 20 30 400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Geometry [dB]

CD

F −

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 16: Geometry, Rural – eMBB, Con-fig A

−180 −160 −140 −120 −100 −80 −60 −400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Coupling Gain [dB]

CD

F −

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 17: Coupling Gain, Rural – eMBB,Config B

−20 −10 0 10 20 30 400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Geometry [dB]

CD

F −

−−

>

3GPP #1

3GPP #2

3GPP #3

3GPP #4

3GPP #5

3GPP #6

3GPP #7

3GPP #8

3GPP #9

3GPP #10

3GPP #11

3GPP #12

3GPP #13

3GPP #14

3GPP #15

3GPP #16

Nomor

Figure 18: Geometry, Rural – eMBB, Con-fig B


Acknowledgement: This work wassupported in part by the European Com-mission under the two 5G-PPP projects“Broadcast and Multicast Communica-tion Enablers for the Fifth-Generationof Wireless Systems” (5G-XCast)(H2020-ICT-2016-2 call, grant number761498) and “5G Mobile Network Ar-chitecture for diverse services, use cases,and applications in 5G and beyond”(5G-MoNArch) (H2020-ICT-2016-2 call,grant number 761445). The viewsexpressed in this contribution are thoseof the authors and do not necessarilyrepresent the projects.

References

[3GP17] 3GPP. Technical SpecificationGroup Radio Access Network;Study on Channel Model for Fre-quencies from 0.5 to 100 GHz(Rel. 14). 3GPP TS 38.901v14.1.1, July 2017.

[Hua18] Huawei. Summary of CalibrationResults for IMT-2020 Self Evalu-ation. 3GPP TSG RAN Meeting#79, RP-180524, March 2018.

[IRa] ITU-R. IMT-2020 Submissionand Evaluation Process. Avail-

able from https://www.itu.int/-en/ITU-R/study-groups/-rsg5/rwp5d/imt-2020/Pages/-submission-eval.aspx.

[IRb] ITU-R. ITU towards “IMT for2020 and beyond”. Availablefrom https://www.itu.int/-en/ITU-R/study-groups/-rsg5/rwp5d/imt-2020/Pages/-default.aspx.

[IR17a] ITU-R. Report M.2410-0 “Min-imum Requirements relatedto Technical Performance forIMT-2020 Radio Interface(s)”.November 2017.

[IR17b] ITU-R. Report M.2411-0 “Re-quirements, Evaluation Criteriaand Submission Templates forthe Development of IMT-2020”.November 2017.

[IR17c] ITU-R. Report M.2412-0“Guidelines for Evaluation ofRadio Interface Technologies forIMT-2020”. October 2017.

[Ita17] Telecom Italia. Proposed wayforward on IMT-2020 submis-sion. 3GPP TSG RAN Meeting#77, RP-172098, 2017.


[SA18a] 3GPP TSG SA. Draft LTI on3GPP 5G Initial DescriptionTemplate. Available fromwww.3gpp.org/ftp/PCG/-PCG 40/docs/PCG40 11.zip,January 2018.

[SA18b] 3GPP TSG SA. LTI on 3GPP5G Preliminary DescriptionTemplate and Self-Evaluation.Available from www.3gpp.org/-ftp/PCG/PCG 41/docs/-PCG41 08.zip, October 2018.

Note:This white paper is provided to youby Nomor Research GmbH. Simi-lar documents can be obtained fromhttp://www.nomor.de. Please supportour work in the social media.

Consultancy Services: Please contactus in case you are interested in our servicesby sending an email to [email protected].

3GPP related Consultancy Services:• Link and System Level Simulations• Research, Analyses and Concept De-

velopment• Demonstration and Prototyping• 3GPP Standardization Support• Technology Training• Patents Support

Technical Areas:• Mobile Communication Networks• Mission Critical Communication• Vehicular Communication• Satellite and Broadcast• Multimedia Delivery and Content

Distribution• Internet of Things

Disclaimer:This paper is provided for informationalpurpose only. We do not accept any re-sponsibility for the content of this newslet-ter. Nomor Research GmbH has no obli-gation to update, modify or amend or tootherwise notify the reader thereof in theevent that any matter stated herein, orany opinion, projection, forecast or esti-mate set forth herein, changes or subse-quently becomes inaccurate. Please notein our assessment(s) we only consideredthose facts known to us and therefore theresults of our assessment / assessmentsare subject to to change due to facts cur-rently not known to us. Furthermore,please note, with respect to our assess-ment(s) different opinions might be ex-pressed in the relevant literature and theremay be some other interpretations whichare scientifically valid.


http://www.nomor.de

mailto:[email protected]

imt-2020 evaluation: calibration of sls -...

Documents