Defense PhD Bouvet

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Iterative receivers for multi-antenna systemsThse prsente devant lINSA de Rennes en vue de lobtention du doctorat dlectronique

Pierre-Jean BOUVETLe 13 dcembre 2005

France Telecom Division Recherche et Dveloppement

08/10/10

Foreword

Forewords s sR&D Unit

QBroadband Wireless Acces / Innovative Radio Interface (RESA/BWA/IRI)Supervisor

QMaryline HELARD, R&D engineer HDR at France Telecom R&D divisionContext

QInternal project: SYCOMORE (research on digital communications) QEuropean project: IST 4-MORE (4G demonstrator based on MIMO and MCCDMA techniques)

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Outline

OutlineI. II. III. V.Introduction Multi-antenna techniques Generic iterative receiver

IV. Optimal space-time codingApplication to MC-CDMA

VI. Conclusion

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Introductio nContext

MIMO techniquesMIMO transmission

Generic iterative receiverObjectives

Optimal spacetime coding

Application to MC-CDMA

Conclusion

Part I: Introduction

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Introductio nContext

MIMO techniquesMIMO transmission

Generic iterative receiverObjectives

Optimal spacetime coding

Application to MC-CDMA

Conclusion

ContextsDigital wireless communications

QHigh spectral efficiency QRobustnessRadio-mobile application

s

QMulti-path propagation Time and frequency selective channel QMobility QMulti-user access

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Introductio nContext

MIMO techniquesMIMO transmission

Generic iterative receiverObjectives

Optimal spacetime coding

Application to MC-CDMA

Conclusion

Multi-antenna (MIMO) transmissionssPrinciple

QMulti-antenna at transmitter and receiver

s

MIMO capacity [Telatar 95]

: covariance of : rank of : singular valuesSISO capacity

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Introductio nContext

MIMO techniquesMIMO transmission

Generic iterative receiverObjectives

Optimal spacetime coding

Application to MC-CDMA

Conclusion

Multi-antenna (MIMO) transmissionssMotivations

QSpectral efficiency gain QPerformance gainSpatial diversity gains Antenna array gains

Capacity gain linear in min(Nt, Nr)

s

Limits

QInterference termsCo Antenna Interference (CAI)

QSpatial correlationAntennas must be sufficiently spaced Rich scattering environment required

QOptimal MIMO capacity exploitationComplex algorithm not well suited for practical implementation Lack of generic schemes

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Introductio nContext

MIMO techniquesMIMO transmission

Generic iterative receiverObjectives

Optimal spacetime coding

Application to MC-CDMA

Conclusion

ObjectivessMulti-antenna transmission

QSpectral efficiency gain QArbitrary antenna configurationNear-optimal reception

s

QMIMO capacity exploitation QIterative (turbo) principle QLow complexity algorithm QMulti-user access

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Transmitte r

Introductio n

MIMO techniquesMIMO Channel

Generic iterative receiverClassification

Optimal spacetime codingLD code

Application to MC-CDMAEquivalent representation

ConclusionCAI

Part II: MIMO techniques

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Transmitte r

Introductio n

MIMO techniquesMIMO Channel

Generic iterative receiverClassification

Optimal spacetime codingLD code

Application to MC-CDMAEquivalent representation

ConclusionCAI

TransmitterInformation bits Coded bits Modulation symbols

Convolution al code

BICM scheme [Caire et al. 98]

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Transmitte r

Introductio n

MIMO techniquesMIMO Channel

Generic iterative receiverClassification

Optimal spacetime codingLD code

Application to MC-CDMAEquivalent representation

ConclusionCAI

MIMO channelsMulti carrier approach (OFDM)Equivalent flat fading MIMO channels

Reduced complexity MIMO equalization (no ISI treatment)

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Transmitte r

Introductio n

MIMO techniquesMIMO Channel

Generic iterative receiverClassification

Optimal spacetime codingLD code

Application to MC-CDMAEquivalent representation

ConclusionCAI

MIMO channelsEquivalent flat fading MIMO channel

Q By assuming ideal symbolinterleaving:

Q T-block Rayleigh fading model Q Represents the optimalperformance of a MIMO-OFDM system over a radio-mobile channel

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Transmitte r

Introductio n

MIMO techniquesMIMO Channel

Generic iterative receiverClassification

Optimal spacetime codingLD code

Application to MC-CDMAEquivalent representation

ConclusionCAI

Classification of MIMO techniquessChannel State Information (CSI) CSI required at Tx and Rx

QEigen beam forming QWater-filling QPre-equalizationCSI required only at Rx

s s

QTreillis based QBlock basedNo CSI required

QDifferential STC QUSTM

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Transmitte r

Introductio n

MIMO techniquesMIMO Channel

Generic iterative receiverClassification

Optimal spacetime codingLD code

Application to MC-CDMAEquivalent representation

ConclusionCAI

Classification of MIMO techniquessChannel State Information (CSI) CSI required at Tx and Rx

QEigen beam forming QWater-filling QPre-equalizationCSI required only at Rx

s s

QTreillis based QBlock basedNo CSI required

QDifferential STC QUSTM

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Transmitte r

Introductio n

MIMO techniquesMIMO Channel

Generic iterative receiverClassification

Optimal spacetime codingLD code

Application to MC-CDMAEquivalent representation

ConclusionCAI

Classification of MIMO techniquessCSI required at Tx and Rx Spatial Data Multiplexing (SDM) [Foschini et al. 96, Wolniansky et al. 98]

QEigen beam forming QWater-filling QPre-equalizationCSI required only at Rx

Space Time Block Coding (STBC) [Alamouti 98, Tarokh et al. 99]

s s

QTreillis based QBlock basedNo CSI required

Linear Precoded STBC [Da Silva et al. 98]

QDifferential STC QUSTM

Algebraical STBC [Damen et al. 03, El Gamal et al. 03]

Linear Dispersion (LD) Code [Hassibi et al. 02]15

Transmitte r

Introductio n

MIMO techniquesMIMO Channel

Generic iterative receiverClassification

Optimal spacetime codingLD code

Application to MC-CDMAEquivalent representation

ConclusionCAI

LD CodeSTC latency: Input block length: STC rate:

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Transmitte r

Introductio n

MIMO techniquesMIMO Channel

Generic iterative receiverClassification

Optimal spacetime codingLD code

Application to MC-CDMAEquivalent representation

ConclusionCAI

Equivalent representationJoint space-time coding and channel representation

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Transmitte r

Introductio n

MIMO techniquesMIMO Channel

Generic iterative receiverClassification

Optimal spacetime codingLD code

Application to MC-CDMAEquivalent representation

ConclusionCAI

Special LD Code

Example s

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Transmitte r

Introductio n

MIMO techniquesMIMO Channel

Generic iterative receiverClassification

Optimal spacetime codingLD code

Application to MC-CDMAEquivalent representation

ConclusionCAI

SolutionsTransmission matrices

s

Reception matrices

s

Equivalent channel matrix

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Transmitte r

Introductio n

MIMO techniquesMIMO Channel

Generic iterative receiverClassification

Optimal spacetime codingLD code

Application to MC-CDMAEquivalent representation

ConclusionCAI

Example: Alamouti Code over channelsTransmission matrices

s

Equivalent model

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Transmitte r

Introductio n

MIMO techniquesMIMO Channel

Generic iterative receiverClassification

Optimal spacetime codingLD code

Application to MC-CDMAEquivalent representation

ConclusionCAI

Co-antenna interference

Desired signal

CAI terms

Nois e

Multi-antenna transmission provides CAI terms

CAI terms can be treated like ISI terms (which were due to the frequency selectivity in SISO transmission)

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Introductio n

MIMO techniquesPrincipl e

Generic iterative receiverMIMO equalizer

Optimal spacetime codingComplexity analysis

Application to MC-CDMAAsymptotical analysis

ConclusionPerformance results

Reception strategies

Part III: Generic iterative receiver

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Introductio n

MIMO techniquesPrincipl e

Generic iterative receiverMIMO equalizer

Optimal spacetime codingComplexity analysis

Application to MC-CDMAAsymptotical analysis

ConclusionPerformance results

Reception strategies

Reception state of the arts sOptimal solution: joint detection

Q ML detection based on a super trellisSub-optimal solutiona.MAP MIMO detection b.SIC, OSIC, PIC detection c.MRC, MMSE, ZF equalization

Optimal performance Very high complexity

1. Disjoint decoding: MIMO detection channel decodingRelative low complexity Optimal performance for orthogonal STC (Alamouti) Sub-optimal performance for non-orthogonal STC

1. Iterative decoding: MIMO detection channel decoding [Berrou et al. 93]a.MAP MIMO detection[Tonello 00, Boutros et al. 00, Vikalo et al. 02]