The I-METRA Project An overview Javier R. Fonollosa http://www.ist-imetra.org

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I-METRA Presentation at the AA Cluster meeting

Outline • Objectives and general description of I-METRA • Adaptive Modulation Schemes for MIMO HSDPA and HSUPA • Link and System level simulations: • Standardised MIMO channel model • Preliminary results on G parameter distribution

• Adaptive Space-Time Processing: • Orthogonal Space-Time Coding and Beamforming • BLAST and linear dispersion codes • Turbo Space-Time Coding

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www.ist-imetra.org

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I-METRA Presentation at the AA Cluster meeting

The I-METRA project •I-METRA builds on the legacy of METRA with the objective of incorporating analysis, development and simulation of adaptive transmission technologies for multipleinput, multiple-output (MIMO) systems •The main emphasis is given to incorporating reconfigurability capabilities in order to allow the radio network, including terminal and base stations, to adjust automatically to traffic, user and channel requirements •The project will investigate the potential implications of these technologies into Systems beyond 3G. 10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Objectives • Quantification of the performance improvement provided by adaptive MIMO technologies in terms of increased data rates and spectrum efficiency • Evaluation of the ability to adjust automatically to different scenarii requirements set up by the traffic, user or channel varying conditions • Implications of the proposed techniques in terms of technical complexity of mobile and base station software and hardware architecture • Compatibility of proposed techniques with current 3GPP specifications as well as the feasibility of incorporating them in future releases • Impact of the MIMO configurations at the mobile terminal and base station in the performance of transmission technologies that are essential in Systems beyond 3G (HSDPA and HSUPA) 10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Adaptive MIMO for HSDPA and HSUPA • The concept of HSDPA has been recently defined in 3GPP for UMTS • HSDPA considers enhancements that can be applied to UTRA to provide very high-speed downlink packet access by means of a highspeed downlink shared channel (HS-DSCH) • I-METRA project is focused on MIMO antenna processing techniques for HSDPA which are related to the evolution of other procedures, such as Adaptive Modulation and Coding (AMC) or Hybrid Automatic Repeat on Request (H-ARQ), in order to include adaptive MIMO techniques in the HS-DSCH structure • HSUPA has received little attention in standardisation so far and is characterised by distinctive requirements 10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Transport Channel Coding Structure for HS-DSCH CRC attachment Code Block Segmentation Channel Coding H-ARQ

RV parameter

Physical Channel Segmentation

... Interleaving ...

Physical Channel Mapping

...

Spreading

...

Modulation 10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Link and System Level Simulation • Link-level simulations alone are not enough to conclude about the performance of a HSDPA system • MIMO HSDPA simulations in I-METRA will be performed in two stages: link-level simulations and system-level simulations. Several look-up tables obtained in the link-level simulation stage should feed the system-level simulations • Look-up tables relating FER values to a given metric, will be computed for different Modulation and Coding (MC) schemes and different MIMO techniques • The MIMO singularity on top of the HSDPA adds some specific requirements to both the link- and system-level simulator, namely: channel modelling, metric definition and HS-DSCH structure 10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Channel Modelling (I) • The I-METRA project will proceed with the MIMO channel model already developed in METRA • This model was filed in 3GPP in Feb. 2001 and after few months, major companies such as Nokia, Lucent, Siemens and Ericsson endorsed the stochastic philosophy of the METRA's MIMO model • This model has the structure of a tapped delay line and its taps are matrices whose size depends on the number of active elements at the transmitting and receiving ends. This model appears as a natural extension of well-accepted ITU profiles • This model is of stochastic nature. It manages to embed the full correlation information of the channel into two correlation matrices defined independently at both ends. A simple Kronecker product is performed to combine these matrices so as to achieve the full characterisation of the correlation properties of a given MIMO channel 10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Channel Modelling (II) • The model in itself is able to address a wide variety of simulation environments. • It can model the time dispersion, the fading and the spatial properties of MIMO channels, using a reduced set of parameters, namely: • Power Delay Profile (PDP) • Power Angular Spectrum (PAS) • Angle of Arrival (AoA) • Angle of Departure (AoD) • Azimuth Spread (AS) • Power Doppler Spectrum (PDoS).

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I-METRA Presentation at the AA Cluster meeting

Channel Metric • For a given data rate, the user performance in a conventional HSDPA channel, usually stated in terms of FER, is reliably predicted using an estimate of the C/I • It is not clear which parameter is the C/I counterpart in a MIMO HSDPA channel • In order to deal with an HSDPA system able to adapt to channel propagation conditions, it is mandatory to define a metric function that maps the channel estimation to the FER on that channel. It is expected that this metric will be different for different MIMO techniques • Additionally, this metric should be simple enough to be transmitted to Node B within the uplink PDCCH-HS using up to 6 bits every TTI (2 ms). 10/04/2002

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I-METRA Presentation at the AA Cluster meeting

How do MIMO systems modify the HS-DSCH structure? CRC attachment Code Block Segmentation Channel Coding H-ARQ Physical Channel Segmentation Interleaving Physical Channel Mapping Spreading Modulation

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I-METRA Presentation at the AA Cluster meeting

How do MIMO systems modify the HS-DSCH structure? CRC attachment Code Block Segmentation Channel Coding H-ARQ Physical Channel Segmentation Interleaving Code reuse and DSTTD

Physical Channel Mapping Spreading Modulation

10/04/2002

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I-METRA Presentation at the AA Cluster meeting

How do MIMO systems modify the HS-DSCH structure? CRC attachment Code Block Segmentation PARC Channel Coding H-ARQ Physical Channel Segmentation Interleaving Code reuse and DSTTD

Physical Channel Mapping Spreading Modulation

10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Code reuse MIMO transmission • Equal transmission rates on each antenna • Coding followed by demultiplexing • Channel code spans space and time dimensions Spreading Code 1

High speed data stream

Spreading Code 2

Coding Interleaving Mapping

D E M U X

... Spreading Code 10

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Scrambling Code

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Scrambling Code

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I-METRA Presentation at the AA Cluster meeting

PARC MIMO Transmission • Distinct transmission rates on each antenna • Demultiplexing followed by coding • Channel code spans time dimension only Spreading Code 1

Spreading Code 2

High speed data stream

Scrambling Code

Coding Interleaving ... Mapping

...

D E M U X

...

Scrambling Code

Spreading Code 10 Coding Interleaving ... Mapping

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I-METRA Presentation at the AA Cluster meeting

System Level Simulations (I) • System-level simulations are mandatory in order to include system attributes such as Fast Cell Selection, H-ARQ or Node B scheduling • System level simulations will take a similar format to that proposed in 3GPP for the evaluation of MIMO techniques for HSDPA. • These will take as input a range of link-level results that will be used in a look-up table - relevant factors may include modulation scheme, coding, redundancy, ratio of in-cell/out-of-cell interference (Gparameter). • The referencing into the look-up table will depend on the chosen MIMO technique and the associated metric. • The G-parameter is important as the interference situation will determine the modulation and coding (for example) chosen by the Node B 10/04/2002

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I-METRA Presentation at the AA Cluster meeting

System Level Simulations (II) 25.00

20.00

% Calls

15.00 Macro Micro 10.00

5.00

0.00 -9

-6

-3

0

3

6

9

12 15 18 21 24 27 30 33 36

G-parameter (dB)

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I-METRA Presentation at the AA Cluster meeting

Adaptive Space-Time Processing • Orthogonal Space-Time Coding and Beamforming with limited state information at the transmit side (CSIT) • BLAST and linear dispersion codes (CSIR only) • Turbo Space-Time Coding (CSIR only)

10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Combining OSTBC and BF (I) • Traditional approach to the design of space-time block codes is based on the minimisation of an upper bound to the pairwise codeword error probability:  d 2 (C k , Cl )  1 P(C k → Cl ) ≤ exp −  2 4σ 2   l (C k → Cl ) =

1 , det A(C k , Cl )

A(C k , Cl ) = (C k − Cl )(C k − Cl )

H

• [Jöngren] proposes to introduce the available state information and minimise 2  (Ck , Cl )  d 1 ˆ P C k → Cl h, h ≤ exp −  2 4σ 2  

(

10/04/2002

)

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d 2 (C k , Cl ) = h H (I N ⊗ A(C k , Cl ))h

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I-METRA Presentation at the AA Cluster meeting

Combining OSTBC and BF (II) • It is assumed that the transmitter has some information on how good the channel estimation is. It therefore uses two different kinds of information: – The actual channel estimation itself: hˆ – A measure of the goodness of the approximation:

R hh hˆ , m h hˆ

Assumed known to the transmitter!!!

• The codes are then designed to minimise: −1 −1 −1 l (C k , Cl ) = m hHhˆ R hh ( ) Ψ C C R m h hˆ − log det Ψ(C k , Cl ) , k l hˆ hh hˆ

Ψ (C k , Cl ) =

10/04/2002

1 −1 (I N ⊗ A(Ck , Cl )) + R hh 2 hˆ 4σ www.ist-imetra.org

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I-METRA Presentation at the AA Cluster meeting

Combining OSTBC and BF (III) • If, in addition, we force C k = W Ck with Ck OSTBC, we can obtain the “optimum” beamformer for this situation.

Symbols

10/04/2002

CK

W

Orthogonal Space-Time Block Coding

Beamforming matrix (one beamformer for code branch)

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I-METRA Presentation at the AA Cluster meeting

Asymptotic situations • Perfect channel state information: R hh hˆ → 0

Traditional beamforming

W → [w M

Symbols

0
0] Left singular vector of the channel matrix

w

CK Orthogonal Space-Time Block Coding

Beamforming vector (only one code branch is processed)

• No channel state information: R

−1 hh hˆ

→0

Symbols

Pure space-time code

1 W→ IM M 10/04/2002

CK

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Orthogonal Space-Time Block Coding

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I-METRA Presentation at the AA Cluster meeting

Simulations

2TX, 1RX 10/04/2002

4TX, 4RX www.ist-imetra.org

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I-METRA Presentation at the AA Cluster meeting

Advantages BF+OSTBC • The architecture provides the optimum performance with respect to both OSTBC and conventional beamforming: BER OSTBC

Proposed Beamformer

Conventional Beamformer

SNR

• Simple processing at the user equipment (OSTBC)

10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Disadvantages BF+OSTBC • Necessity of MIMO channel feedback: vector quantisation (In current HSDPA specifications only 2 bits/slot are available ) • Perfect knowledge of the estimation statistics is assumed and, even so, mild gains are obtained. Behaviour in a practical situation? • Relatively high computational requirements at Node B. A new beamformer must be calculated at each channel update, and a complex optimisation procedure must be carried out for non-diagonal covariance matrices. • A new beamformer matrix must be calculated every time the transmission rate is changed. The architecture not very suitable from the re-configurability point of view.

10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Linear Dispersion Codes (I) • Each symbol is multiplied by a transmit matrix over a particular spacetime support. For the real-valued (BPSK) case: Linear Dispersion Block Coding

Q

X = ∑ sk C k k =1

Space-time coding matrix

Symbols

S/P

...

• This architecture subsumes OSTBC and BLAST as special cases:

C1

CQ

1 0  0 1 C1 =   C 2 = − 1 0 0 1    

(2 x 2) Alamouti code

1 0 0 1  0 0  0 0  C1 =  C2 =  C3 =  C4 =      0 0  0 0  1 0 0 1  10/04/2002

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(2 x 2) V-BLAST 24

I-METRA Presentation at the AA Cluster meeting

Linear Dispersion Codes (II) • The channel knowledge is only assumed at the receiver. The code matrices are designed as follows: ρ 1   T  max E H log det I NT + H (Cq )H (Cq )  Cq T M   

averaged over all possible realisations of the channel. • The receiver can be almost as simple as in OSTBC. Linear receivers are viable. • Depending the number of signals sent (Q), the block length (T), and the size of the constellation of the symbols (r bits/symbol), the overall transmit rate will be Q R = log 2 r T 10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Implementation LD Codes ADVANTAGES

DISADVANTAGES

• Ease of rate re-configurability in a MIMO architecture. • Given the possibility of linear receivers, the channel performance metric seems easily computable. • The architecture admits the possibility of more receive than transmit antennas.

10/04/2002

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• No channel state information is used by the transmitter. • The codes are optimised for particular channel statistics.

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I-METRA Presentation at the AA Cluster meeting

Turbo Codes: Encoder • Standard Turbo Codes employ two parallel Recursive Systematic Convolutional (RSC) Codes concatenated via an interleaver. • The systematic bit and the two parity bits are rearranged in a serial order. Systematic bit

RSC

p

P/S Parity bits

RSC

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I-METRA Presentation at the AA Cluster meeting

Turbo Codes: Decoder • Two soft output decoders serially concatenated via interleavers • Each decoder takes three inputs: a received systematic bit, a received parity bit and soft a-priori information from the other encoder • 5-10 iterations of decoding are used • On the last iteration, a hard decision is applied on the soft outputs

Soft Decoder

p Soft Decoder

p -1

p 10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Space Time Turbo Codes • Space Time Codes (STC) are codes designed for Multiple Inputs and Multiple Outputs (MIMO) systems • Space Time Turbo Codes (STTC) are STC codes which use the concept of iterative turbo decoding

10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Simple STTC Scheme • A possible simple scheme of STTC is using the standard Turbo architecture, but simultaneously transmitting the bits through a few transmit antennas. Thus, achieving both coding diversity, and transmit diversity

RSC

p RSC

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I-METRA Presentation at the AA Cluster meeting

General STTC Scheme • In a more general STTC scheme, the transmitter consists of a general encoder for coding diversity, serially followed by a general STC for transmit diversity. • The receiver has a joint decoding and demodulating algorithm based on the Turbo principle.

Channel Encoder

10/04/2002

p

STC

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I-METRA Presentation at the AA Cluster meeting

Hochwald & Brink’s Scheme

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I-METRA Presentation at the AA Cluster meeting

Tujkovic’s Scheme: Encoder (Recursive) STTC

Puncture and/or multiplex

Bit-level interleaver Recursive STTC

• Interleaving on bit-level (~1.5 dB gain compared to symbol level) • Only one component encoder connected to outputs at given time • If puncturing is not applied, bandwidth efficiency is halved 10/04/2002

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I-METRA Presentation at the AA Cluster meeting

Tujkovic’s Scheme: Decoder

symbol MAP 1

sym/ + bits

interleaver

bit/ sym

symbol MAP 2

bit/ sym

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interleaver

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+

sym/ bits

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