Fundamental Performance Limits on Time of Arrival Estimation Accuracy with 5G Radio Access

49 Pages·2017·8.52 MB·English

DEGREE PROJECT IN ELECTRICAL ENGINEERING,
SECOND CYCLE, 30 CREDITS
STOCKHOLM, SWEDEN 2017
Fundamental Performance Limits
on Time of Arrival Estimation
Accuracy with 5G Radio Access
DEHAN LUAN
KTH ROYAL INSTITUTE OF TECHNOLOGY
SCHOOL OF ELECTRICAL ENGINEERING

Abstract
5G radio access technology stimulates new use cases and emerging business
models, evolving the world to become a fully mobile and connected network
society, expected to be operational by 2020. To enable ultra-high reliable and
highly precise features, there are more stringent positioning accuracy require-
ments for location based services and E911 emergency calls, targeting at both
indoorandoutdooruserswhichincludehumans,devices,vehiclesandmachines.
In currently deployed Long Term Evolution (LTE) networks, Observed Time
Di↵erence of Arrival (OTDoA) positioning is acting as one of the User Equip-
ment(UE)localizationtechniques. ThepositioningaccuracyinOTDoAmethod
depends on various factors, e.g. network deployment, signal propagation con-
dition and properties of Positioning Reference Signal (PRS). For a given de-
ployment and propagation scenario, significant improvements of positioning ac-
curacyisachievablebyappropriatelyredesigningthePRSwith5Gradioaccess.
Inthisthesis,fundamentalperformancelimits(i.e. CramerRaoLowerBounds)
on Time of Arrival (ToA) estimation are derived respectively considering fre-
quency selective channel with additive white noise, carrier frequency o↵set and
Wiener phase noise. Particularly, the e↵ects of flexible bandwidth, subcarrier
spacingandpowerallocationonToAestimationaccuracyhavebeeninvestigated
in di↵erent settings based on corresponding performance bounds. Furthermore,
theperformancelimitsonToAestimationcanbetranslatedintoUEpositioning
accuracy for a given deployment scenario. Overall, the thesis has built valuable
insights on PRS design and waveform optimization for 5G based positioning.

Sammanfattning
5G radioteknik stimulerar nya anv¨andaromr˚aden och nya a↵¨arsmodeller samt
utvecklar v¨arlden till att bli ett helt mobilt och anslutet n¨atverkssamh¨alle,
vilket f¨orv¨antas vara i drift till˚ar 2020. F¨or att m¨ojligg¨ora ultrah¨og p˚alitlighet
och h¨ogprecisionsfunktionalitet kr¨avs det str¨angare krav p˚a positionering f¨or
platsbaserade tj¨anster och n¨odsamtal, som riktar in sig p˚a b˚ade inomhus- och
utomhusanv¨andare vilket inkluderar m¨anniskor, enheter, fordon och maskiner.
I det nuvarande distribuerade LTE-n¨atverket fungerar Observed Time Di↵er-
ence of Arrival-positionering (OTDoA)-positionering som en av lokalisering-
steknikernaf¨oranv¨andarutrustning(UE).PositioneringsnoggrannheteniOTDoA-
metoden beror p˚a olika faktorer, t.ex. n¨atverksutbyggnad, signalutbrednings-
f¨orh˚allande och egenskaper f¨or positions referenssignal (PRS). F¨or ett visst
installations- och utbredningsscenario kan betydande f¨orb¨attringar av position-
snoggrannheten uppn˚as genom att omforma PRS p˚a l¨ampligt s¨att.
I detta examensarbetet unders¨oks de grundl¨aggande prestandabegr¨ansningarna
(dvsCramerRaoLowerBounds)vidAnkomsttid(ToA)h¨arl¨addamedavseende
p˚afrekvensselektivakanalermedadditivtvittbrus,b¨arfrekvensf¨orskjutningoch
Wienerfasbrus. I synnerhet, unders¨oks e↵ekten av flexibel bandbredd, subcar-
rieravst˚and och e↵ektallokering p˚a ToA-estimeringsnoggrannhet underso¨kts i
olika inst¨allningar baserat p˚a prestandabegr¨ansningarna. Vidare kan prestand-
abegr¨ansningarna f¨or ToA-estimering ¨overs¨attas till UE-positionsnoggrannhet
f¨or ett givet implementationsscenario. Slutligen s˚a har detta examensarbetet
gett viktiga insikter om positionering av referenssignaldesign och v˚agformsopti-
mering f¨or 5G-baserad positionering.

Acknowledgment
First of all, I’d like to show my gratitude to master thesis supervisor, Mr. Ali
Zaidi, from Ericsson Research, who has provided me opportunity and guid-
ance on this promising topic. This working thesis has helped me to sort out
knowledge pieces and sew them together. From working in the industry, I also
broadened my sights and gained experience.
Also, I’d like to extend my gratitude to my examiner, Mr. Tobias Oechtering,
Associate Prof. from KTH University, who has given me helps and encourage-
ments during these months.
Additionally, I would like to thank Navneet Agrawal, Maria Edvardsson, Zhao
Wang, Vicent Moles Cases, Hieu Do, Wanlu Sun, Yiqing Wang from Ericsson
who havs ever inspired me and provided great helps.

Contents
1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Problem Formulation and Methodology . . . . . . . . . . . . . . 2
1.3 Societal and Ethical Aspects . . . . . . . . . . . . . . . . . . . . 3
1.4 Pevious Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.5 Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.6 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2 Background 6
2.1 Positioning in Future 5G Networks . . . . . . . . . . . . . . . . . 6
2.1.1 OTDoA Positioning . . . . . . . . . . . . . . . . . . . . . 6
2.1.2 ToA Estimation . . . . . . . . . . . . . . . . . . . . . . . 8
2.1.3 Positioning Reference Signal. . . . . . . . . . . . . . . . . 9
2.2 Fundamental Performance Limit . . . . . . . . . . . . . . . . . . 11
2.2.1 Minimum Variance Unbiased Estimation . . . . . . . . . . 11
2.2.2 Cramer Rao Lower Bound . . . . . . . . . . . . . . . . . . 11
3 Derivatons - Cramer Rao Lower Bounds on ToA Estimation 14
3.1 AWGN Channel . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.2 Frequency Selective Channel. . . . . . . . . . . . . . . . . . . . . 16
3.2.1 CSIR - Channel State Information at Receiver . . . . . . 17
3.2.2 CSIT - Channel State Information at Transmitter . . . . 17
3.2.3 No CSI - No Channel State Information . . . . . . . . . . 17
3.3 Carrier Frequency O↵set/Doppler Shift . . . . . . . . . . . . . . 19
3.4 Wiener Phase Noise . . . . . . . . . . . . . . . . . . . . . . . . . 20
4 Simulations and Result Analysis - Flexible Parameter Exploit 22
4.1 Bandwidth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4.2 Subcarrier Spacing . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.3 Power Allocation . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
5 Conclusions and Future Work 33
5.1 Main Findings on ToA Performance . . . . . . . . . . . . . . . . 33
5.2 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.3 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
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List of Figures
1.1 ToA Estimation Uncertainty in OTDoA Positioning . . . . . . . 2
2.1 Dense Urban and Indoor Scenario. . . . . . . . . . . . . . . . . . 7
2.2 OTDoA Multilateral Positioning Method . . . . . . . . . . . . . 8
2.3 PRS in Physical Resource Block . . . . . . . . . . . . . . . . . . 9
2.4 Frequency Spectrum of OFDM Waveform . . . . . . . . . . . . . 10
2.5 PRS in Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.6 Cramer Rao Lower Bound on Variance of Unbiased Estimator . . 11
4.1 Bandwidth Exploit on ToA Estimation in AWGN Channel . . . 23
4.2 Specific Channel Frequency Response . . . . . . . . . . . . . . . 24
4.3 Bandwidth Exploit on ToA Estimation in Multipath Channel . . 25
4.4 BandwidthExploitonToAEstimationwithWienerPhaseNoise
in AWGN Channel . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.5 Subcarrier Spacing Exploit on ToA Estimation in AWGN Channel 26
4.6 Subcarrier Spacing Ratio in AWGN Channel . . . . . . . . . . . 27
4.7 SubcarrierSpacingExploitonToAEstimationinMultipathChan-
nel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.8 SubcarrierSpacingExploitonToAEstimationwithWienerPhase
Noise in AWGN Channel . . . . . . . . . . . . . . . . . . . . . . 28
4.9 Power Allocation Exploit on ToA Estimation in AWGN Channel 29
4.10 Monte Carlo Simulation for Power Optimization . . . . . . . . . 30
4.11 Power Allocation Exploit on ToA Estimation with No CSI in
Multipath Channel . . . . . . . . . . . . . . . . . . . . . . . . . . 30
4.12 WienerPhaseNoiseVarianceExploitonToAEstimationinAWGN
Channel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
4.13 PowerAllocationExploitonToAEstimationwithWienerPhase
Noise in AWGN Channel . . . . . . . . . . . . . . . . . . . . . . 32
5.1 Main Findings on ToA Performance . . . . . . . . . . . . . . . . 33
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