IDMA Slides P.ping

7/24/2019 IDMA Slides P.ping

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Interleave Division Multiple Access

(IDMA)

Lihai Liu, Raymond Leung and Li Ping

Department of Electronic and EngineeringCity University of Hong Kong


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Outline

Introduction Iterative detection

Performance evaluation

Multi-user gain in fading channels Other applications

Conclusions


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Outline




Conclusions


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The Focus of this Talk

We will mostly focus on up-link multiple access channels

(MAC), although the results can be applied to down-linkbroadcasting channels (BC).

For detail, see

Li Ping, Lihai Liu, K. Y. Wu and W. K. Leung, "Interleave-division multiple-

access,"IEEE Trans. on Wireless Commun, pp. 938-947, April 2006.


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Desired Features of a Good Up-link Scheme

low receiver cost

de-centralized (i.e., asynchronous) control simple treatment of ISI cross-cell interference mitigation diversity against fading

high power efficiency high spectral efficiency suitable for both wide or narrow band transmission flexible rate adaptation

multi-user gain (detailed tomorrow).

A conventional method (such as TDMA, FDMA, CDMA etc)cannot provide all these features simultaneously. Is there a unifiedsolution? Yes!


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Problems with TDMA, FDMA and CDMA

TDMA and FDMA require centralized control and strict

synchronization. They are not flexible in many situations. Forexample, it is quite difficult to synchronize an ad hoc network.

TDMA and FDMA are strictly sub-optimal in fading environments.In particular, TDMA and FDMA (and OFDMA) can be seriously

inferior in MIMO channels. This is related to multi-user gain.

CDMA is flexible regarding synchronization. However, CDMA is a

low-rate scheme by nature. It is difficult to provide high single-user

throughput with CDMA.


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Multi-User Gain (MUG)

From information theory, allowing multiple users to transmit

simultaneously can lead to significantly power reduction. Thisadvantage is referred to as multi-user gain.

See:

Peng Wang, Jun Xiao, and Li Ping, "Comparison of orthogonal and non-

orthogonal approaches to future wireless cellular systems,"IEEE Vehicular

Technology Magazine, vol. 1, no. 3, pp. 4-11, Sept. 2006.


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Multi-User Gain in Fading Channels

Up-link, sum-rate = 8 bits/chip, Pout= 0.01

about12dB

channelcapacity


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An Example of Multi-User Gain

For details, see

Li Ping, Qinghua Guo, and Jun Tong, The OFDM-IDMA approach towireless communication systems,IEEE Wireless Commun. Mag., June 2007.

Multi-usergain

OFDM-IDMA

OFDMA

Average transmission power


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The Problem with CDMA

0

0.5

1

1.5

2

2.5

3

3.5

4

-2 0 2 4 6 8 10 12 14

Eb/N0 (dB)

S

p

ectral

efficien

cy

(b

its/ch

ip

)

Matched Filter

Optimal

xxx

Multi-userdetection isnecessary to getinto this range.


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Shannon showed in 1940s that optimal communication systems can

be built using randomly generated signals.

However, random coding has long been regarded as genius

theoretical concept, rather than a practical method. The advent ofturbo coding showed that Shannons is actually very practical, atleast for binary error correction codes.

Turbo and LDPC codes have solved the problem for random binarycode design. How about other applications?

It turns out that it is very easy to achieve random signaling in a

multi-user environment.

What is an Optimal System

t


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Here is an engineering approach to random coding based

on interleaving


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IDMA System Model

h1

hk

hK n

1d

kd

Kd

Transmitter for user-1

1ENC1

Transmitter for user-k

kENCk

Transmitter for user-K

.

.

KENCK

...

..

.

=

+=K

k

kkh1

nxr

x1

xk

xK


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CDMA System Model

h1

hk

hK n

1d

kd

Kd


ENC1


ENCk


ENCK

...

..

.

=

+=K

k

kkh1

nxr

x1

xk

xK

s1

sk

sK


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Comparison of IDMA and CDMA

h1

hk

hK n

1d

kd

Kd


ENC1


ENCk


ENCK

...

...

x1

xk

xK

1

k

K

h1

hk

hK n

1d

kd

Kd


ENC1


ENCk


ENCK

...

...

x1

xk

xK

s1

sk

sK

IDMA CDMA

Interleaving in IDMA does not incur rate loss, but spreading inCDMA incurs rate loss.


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A Factor Graph for a LDPC Code


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A Factor Graph for a CDMA System

User 1 information bits



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A Factor Graph for an IDMA System




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Outline




Conclusions


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The Iterative Principle

The optimal approach is to consider two constraints jointly.

A sub-optimal approach is to handle one constraint at a time using aniterative process.

User 1:

User 2:

coding constraintt

User 3:

ReceivedSignal:

superpositionconstraint


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IDMA System Model

h1

hk

hK n

1d

kd

Kd

user-1

ENC1

user-k

ENCk

user-K

ENCK

...

...

=

+=K

k

kkh1

nxr

x1

xk

xK

s1

sk

sK


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Message Passing at Channel Nodes




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Gaussian Approximation Detection

Path model and Gaussian approximation

Estimation:

( ) ( )k k k

h x j j+=

1( ) ( ) ( )

K

k k

kr j h x j n j

== +

( )

2

2

( ( ) E( ( )) )exp( )

Pr( ( ) 1) 2Var( ( )) 2log = log ( ) E( ( ))

( ( ) E( ( )) )Pr( ( ) 1) Var( ( ))

exp( )2Var( ( ))

k k

k k kk

k kk k

k

r j j h

x j j hr j j

r j j hx j j

j

= + =

+=

Gaussian

( ) ( )2

( ) = ( ) E( ( ))Var( ( ))

kk k

k

he x j r j j

j

Some details:


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Chip-by-Chip (CBC) Detection Algorithm

Step 1.

Step 2.

Step 3.

( ) ( ) ( ) ( )E ( ) E E ( )k k kr jj h x j =

( ) ( )1

E ( ) E ( )K

k k

k

r j h x j

=

=

( ) ( )2

( ) ( ) E( ( ))Var( ( ))

kk k

k

he x j r j j

j=

( ) ( )2

1

Var ( ) Var ( )K

k k

k

r j h x j

=

=

( ) ( ) ( )2

( )Var ( ) Var Var ( )k k kr jj h x j =

Notes:(1) There is no matrix operation.(2) E(xk(j) and Var(xk(j)) are the feedback from the decoders.


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A Factor Graph for an IDMA System




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Chip-by-Chip Multiuser Detection

Chip-by-ChipProcessing

APPDEC-k

k

1k

r={r(j)}

APPDEC-11

1

1


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Complexity

6 additions and 6 multiplications per chipper iteration peruser.

Complexity (per user) is independent of user number K.

Comparison: To achieve good performance, the cost for MMSECDMA multi-user detection is O(K2) due to matrix operations.


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Un-coded IDMA

1.E-05

1.E-04

1.E-03

1.E-02

1.E-01

1.E+00

0 2 4 6 8 10 12 14 16 18 20 22 24

Average Eb/N0(dB)

BER

8 users 64 users

single-user

Rate-1/8 repetition coding


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Convolutional-Repetition Coded IDMA

(a)(b)

1.E-05

1.E-04

1.E-03

1.E-02

1.E-01

1.E+00

0 2 4 6 8 10 12 14 16 18 20 22

Average Eb/N0 (dB)

BER

IDMA

8 users

IDMA

16 users

IDMA

32 usersIDMA

64 users

CDMA

6 users

matched filter

capacities

Rate and rate repetition coding. Overall rate =1/8.


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Outline



Multi-user gain in fading channels

Other applications

Conclusions


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The Basic Principle

The analysis of an iterative decoder or iterative multi-user detectoris usually a difficult task. For example, for an iterative CDMAmulti-user detector, the impact of spreading sequences are acomplicated issue.

However, for IDMA, it is quite straightforward. This is because theoperation is at the chip level. We detect a chip a time, which is veryeasy to analyze.

For Detail, see

Lihai Liu, Jun Tong, and Li Ping, "Analysis and optimization of CDMA systems

with chip-level interleavers,"IEEE J. Select. Areas Commun., pp. 141-150,

January 2006.


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IDMA Performance Evaluation

)()()(

)()()(

1

jnjxhpjxhp

jnjxhpjr

kiiiikkk

K

k

kkk

++=

+=

=

( )

+=ki

old

iiii

kknewkSNRfhp

hpSNR 2)(2

2

)(||

||

Gaussian

kSNR k = ,0)0(

Received chip:

SNR evolution:

Initialization:


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SNR Evolution for an IDMA Detector

ESE

APPDEC-k

1k

r={r(j)}

APP

DEC-1

k

11

1

{e(x1(j))}

{E(x1(j))}

{e(xk(j))}

{E(xk(j))}

Iterativedetector

ESE

f()

r={r(j)}

f()

SNR1

SNRk

Variance1

Variancek

Evolutionprocess


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SNR Evolution for an IDMA DecoderThe iterative detector can be characterized by the following SNRevolution process:

This is much simpler and faster than simulation.

2( )

2 ( ) 2

| |

| | ( )new k k

k old

i i i i

i k

h pSNR

h p f SNR

=+

ESE

f()1

k

r={r(j)}

f()

SNR1

SNRk

k

11

1Variance1

Variancek

Evolution

process

Evolutionformula


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IDMA Performance Evaluation

DECkSNRk

f(SNRk)

f-function of a rate R=1/2

ideal code

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