Thèse présentée devant l’insa de Rennes en vue de l’obtention du doctorat d’Électronique

• Thèse présentée devant l’INSA de Rennes en vue de l’obtention du doctorat d’Électronique

Foreword

• R&D Unit

• Broadband Wireless Acces / Innovative Radio Interface (RESA/BWA/IRI)

• Supervisor

• Maryline HELARD, R&D engineer HDR at France Telecom R&D division

• Context

• Internal project: SYCOMORE (research on digital communications)
• European project: IST 4-MORE (4G demonstrator based on MIMO and MC-CDMA techniques)

Outline

• Introduction

• Multi-antenna techniques

• Generic iterative receiver

• Optimal space-time coding

• Application to MC-CDMA

• Conclusion

Context

• Digital wireless communications

• High spectral efficiency
• Robustness

• Radio-mobile application

• Multi-path propagation
• Mobility
• Multi-user access

Multi-antenna (MIMO) transmissions

• Principle

• Multi-antenna at transmitter and receiver

• MIMO capacity [Telatar 95]

Multi-antenna (MIMO) transmissions

• Motivations

• Spectral efficiency gain
• Performance gain
• Spatial diversity gains
• Antenna array gains

• Limits

• Interference terms
• Co Antenna Interference (CAI)
• Spatial correlation
• Antennas must be sufficiently spaced
• Rich scattering environment required
• Optimal MIMO capacity exploitation
• Complex algorithm not well suited for practical implementation
• Lack of generic schemes

Objectives

• Multi-antenna transmission

• Spectral efficiency gain
• Arbitrary antenna configuration

• Near-optimal reception

• MIMO capacity exploitation
• Iterative (turbo) principle
• Low complexity algorithm
• Multi-user access

Transmitter

MIMO channel

• Multi carrier approach (OFDM)

MIMO channel

• Equivalent flat fading MIMO channel

Classification of MIMO techniques

• CSI required at Tx and Rx

• Eigen beam forming
• Water-filling
• Pre-equalization

• CSI required only at Rx

• Treillis based
• Block based

• No CSI required

• Differential STC
• USTM

Classification of MIMO techniques

• CSI required at Tx and Rx

• Eigen beam forming
• Water-filling
• Pre-equalization

• CSI required only at Rx

• Treillis based
• Block based

• No CSI required

• Differential STC
• USTM

Classification of MIMO techniques

• CSI required at Tx and Rx

• Eigen beam forming
• Water-filling
• Pre-equalization

• CSI required only at Rx

• Treillis based
• Block based

• No CSI required

• Differential STC
• USTM

LD Code

Equivalent representation

Special LD Code

Solution

• Transmission matrices

• Reception matrices

• Equivalent channel matrix

Example: Alamouti Code over channel

• Transmission matrices

• Equivalent model

Co-antenna interference

Reception state of the art

• Optimal solution: joint detection

• ML detection based on a “super trellis”

• Sub-optimal solution

• Disjoint decoding: MIMO detection  channel decoding
• MAP MIMO detection
• SIC, OSIC, PIC detection
• MRC, MMSE, ZF equalization
• Iterative decoding: MIMO detection  channel decoding [Berrou et al. 93]
• MAP MIMO detection
• [Tonello 00, Boutros et al. 00, Vikalo et al. 02]
• Filtered based MIMO equalization
• [Sellathurai et al. 00, Gueguen 03, Witzke et al. 03]

Reception state of the art

• Optimal solution: joint detection

• ML detection based on a “super trellis”

• Sub-optimal solution

• Disjoint decoding: MIMO detection  channel decoding
• MAP MIMO detection
• SIC, OSIC, PIC detection
• MRC, MMSE, ZF equalization
• Iterative decoding: MIMO detection  channel decoding [Berrou et al. 93]
• MAP MIMO detection
• [Tonello 00, Boutros et al. 00, Vikalo et al. 02]
• Filtered based MIMO equalization
• [Sellathurai et al. 00, Gueguen 03, Witzke et al. 03]

Principle

• Application of the turbo-equalization concept to MIMO

MIMO equalizer (1)

• MMSE based soft interference cancellation (MMSE-IC)

• [Glavieux et al. 97, Wang et al. 99, Reynolds et al. 01, Tüchler et al. 02, Laot et al. 05]

• MMSE optimization of both filters

MIMO equalizer (2)

• Optimal solution: MMSE-IC

• Time invariant approximation: MMSE-IC(1)

MIMO equalizer (3)

• Matched filter approximation: MMSE-IC(2)

• Zero-Forcing solution: ZF-IC

Complexity analysis (MIMO equalizer)

Asymptotical analysis

• Asymptotical performances = Genie aided receiver

• Asymptotical equivalent channel

Asymptotical diversity

• Pair-wise error probability

• Chi-square approximation and Chernoff bound

Asymptotical diversity

• Proposed definition of the space-time diversity

• Total diversity exploited by both channel and space-time coding

• Modified Singleton Bound [Gresset et al. 04]

Performance results: simulation conditions

• Theoretical independent T-Block Rayleigh flat fading MIMO channel

• Non recursive non systematic convolutional code (133,171)o, K=7

• SOVA algorithm for channel decoding

• No spatial correlation

• Normalized BER

• Asymptotical curve: Matched filter Bound (MFB)

• Optimal curve: AWGN decoupled

Performance results: Jafarkhani code

Performance results: SDM

Performance results: SDM overloaded

Synthesis

• Derivation of a MMSE iterative receiver for generic MIMO transmission

• Reduced complexity versus MAP based iterative algorithm

• Asymptotical analysis

• Proposition of an estimation of the space-time coding diversity

• Simulation results

• MMSE-IC(1) tends towards the MFB curve whichever space-time coding scheme is used
• MMSE-IC(1) still works in case of rank degenerated channel matrix
• MMSE-IC(2) and ZF-IC converge when CAI terms are quite low and/or for small order modulation

Optimality conditions

• Maximizing data rate

• Maximizing space-time coding diversity

• Minimizing and

• Minimizing the non orthogonal terms of

Optimality conditions

• Maximizing data rate

• Maximizing space-time coding diversity

• Minimizing and

• Minimizing the non orthogonal terms of

Maximizing data rate

• Ergodic Capacity

• High SNR approximation (Foschini et al. 96)

Maximizing the diversity

• Assuming ML detection

• Pairwise error probability analysis
• Diversity gain maximization
• TAST [El Gamal et al. 03], FDFR [Ma et al. 03]

• Assuming MMSE-IC reception

• Asymptotical analysis
• Space-time coding diversity maximization
• Sufficient condition: “Along a space-time coded block, each data symbol must be transmitted uniquely by each antenna”

Summary

• Conditions:

• STC construction rule:

• “During Nt symbol durations, min(Nt,Nr) data symbols have to be uniquely transmitted by the Nt antennas”

Diagonal Threaded Space Time (DTST) coding

Example over a channel

Performance results

• 4 transmit antennas and 2 receive antennas

• Channel model: T-block Rayleigh flat fading

• No spatial correlation

• Reception

• If S is orthogonal: MRC
• If S is non orthogonal: MMSE-IC with 5 iterations

• Optimal performance: AWGN decoupled

• Corresponds to virtual parallel AWGN channels

System Parameters

Ergodic capacity

BER Performance

Capacity at BER=10-4

MC-CDMA

• Introduced in 93 [Yee et al. 93, Fazel et al. 93]

• Aim

• to spread multi-user information in the frequency domain

• Principle

• Combination of CDMA and OFDM techniques

• Benefits

• Robustness against multi-path channels
• Multi-user flexibility
• Low multi-access interference (MAI) in downlink scenario

MIMO MC-CDMA Transmitter

Equivalent model

• Equivalent channel matrix

• Receive signal

• Receiver algorithm

• Since S’ is a special LD code, proposed MMSE-IC receiver can be used

Multi-user iterative receiver

• MMSE-IC (1) solution

• Full load approximation

Performance results: 4x2 Bran E channel

• Bran E model

Performance results: 4x2 Bran E channel

• DA code

Performance results: 4x2 Bran E channel

Performance results: 4x2 Bran E channel

General conclusion

• MIMO capacity can be efficiently exploited by iterative processing

• MMSE-IC based solutions lead to low complexity algorithm (especially comparing to MAP based solution)

• High order modulations are suitable
• High number of antennas can be considered

• MMSE-IC receiver can be derived for MC-CDMA transmission

• The behavior of MMSE-IC receiver over realistic channel including channel estimation is satisfactory

Major contributions

• Proposition and analysis of a MIMO iterative receiver

• Generic structure
• Reduced complexity algorithms
• Theoretical analysis (complexity and asymptotical behavior)

• Proposition of new optimal LD codes

• DTST

• Application of iterative reception

• MC-CDMA
• Linear precoding

• Performance results

• Theoretical channels
• Realistic channels (channel estimation and spatial correlation)

Future prospects

• Iterative channel estimation

• Joint channel estimation and decoding

• Turbo-codes instead of convolutional codes as channel coding

• Multi-loop iterative scheme

• Real channels

• Realistic spatial correlation model

• Application to OFDMA

• Implementation issues

Publications and patents

• International Conference

• P-J. Bouvet and M. Hélard, «Near optimal performance for high data rate MIMO MC-CDMA scheme», MC-SS 05
• B. Le Saux, M. Hélard and P-J. Bouvet, « Comparison of coherent and non-coherent space time schemes for frequency selective fast-varying channels », IEEE ISWCS 05
• P-J. Bouvet, M. Hélard and V. Le Nir, «Low complexity iterative receiver for linear precoded OFDM», IEEE WiMob 05
• P-J. Bouvet and M. Hélard, «Efficient iterative receiver for spatial multiplexed OFDM system over time and frequency selective channels», WWC 05
• P-J. Bouvet, M. Hélard and V. Le Nir, «Low complexity iterative receiver for non-orthogonal space-time block code with channel coding», IEEE VTC Fall 04
• P-J. Bouvet, V. Le Nir, M. Hélard and R. Le Gouable, «Spatial multiplexed coded MC-CDMA with iterative receiver» IEEE PIMRC 04

Publications and patents

• International Conference (cont’d)

• P-J. Bouvet, M. Hélard and V. Le Nir, «Low complexity iterative receiver for linear precoded MIMO systems», IEEE ISSSTA 04
• M. Hélard, P-J. Bouvet, C. Langlais, Y. M. Morgan and I. Siaud, «On the performance of a Turbo Equalizer including Blind Equalizer over Time and Frequency Selective Channel. Comparison with an OFDM system», Symposium Turbo 03
• C. Langlais, P-J. Bouvet, M. Hélard and C. Laot, «Which Interleaver for turbo-equalization system on frequency and time selective channels for high order modulations ? », IEEE SPAWC 03

• National conference

• B. Le Saux, M. Hélard and P.-J Bouvet, «Comparaison de technique MIMO cohérents et non-cohérentes sur canal rapide sélectif en fréquence», MajeSTIC 05

Publications and patents

• Patents

• P-J Bouvet and M. Hélard, « Procédé d’émission d’un signal ayant subi un précodage linéaire, procédé de réception, signal, dispositifs et programmes d’ordinateur correspondant », Nov. 05
• J-P. Javaudin and P-J. Bouvet, «Procédé de codage d'un signal multiporteuse de type OFDM/OQAM utilisant des symboles à valeurs complexes, signal, dispositifs et programmes d'ordinateur correspondants», May 05
• J-P. Javaudin and P-J. Bouvet, «Procédé de décodage itératif d'un signal OFDM/OQAM utilisant des symboles à valeurs complexes, dispositif et programme d'ordinateur correspondants», May 05
• P-J. Bouvet and M. Hélard, «Procédé de réception itératif d'un signal multiporteuse à annulation d'interférence, récepteur et programme d'ordinateur correspondants», March 05

Publications and patents

• Patents (cont’d)

• P-J. Bouvet, M. Hélard and V. Le Nir, « Procédé de réception itératif pour système de type MIMO, récepteur et programme d'ordinateur correspondants », Nov. 04
• P-J. Bouvet, V. Le Nir and M. Hélard, « Procédé de réception d'un signal ayant subi un précodage linéaire et un codage de canal, dispositif de réception et produit programme d'ordinateur correspondants », Jun. 04
• M. Hélard, P-J. Bouvet, V. Le Nir and R. Le Gouable, « Procédé de décodage d'un signal codé à l'aide d'une matrice espace-temps, récepteur et procédé de codage et décodage correspondant », Sept. 03