wireless mobile communication and transmission lab. chapter 8 application of error control coding

Wireless Mobile Communication and Transmission Lab.

Chapter 8

Application of Error Control Coding

2/36Wireless Mobile Communication and Transmission Lab.

Outline

History ： 2G ——3G——4GECC Application For 3G Adaptive Modulation and Coding (AMC)


Outline



History

CDMA OneI S-95-A

CDMA OneI S-95-B

CDMA20001x

CDMA20001xEV-DO/ DV

CDMA20003x

GSM GPRS

HSDPA

EDGE

Newoperator

WCDMA

TD-SCDMA

2G B3G(4G)3G2. 75G2. 5G

1995 1999 2000 2001/ 2/ 3 2002/ 3/ 4 2004/ 6

LTE

2007/ 10

Wi MAXI EEE std802. 16

proposedby Chi na

802. 16e, f , g, h, i , j , k 802. 16m


Outline

History ： 2G ——3G （ IMT-2000 ） —— B3G （ IMT-A ）—— 4G

ECC Application For 3G Adaptive Modulation and Coding (AMC)


Error Coding

3G——IMT-2000:1 、 WCDMA2 、 CDMA20003 、 TD-SCDMA4 、 WiMAX


WCDMA

Usage of channel coding scheme and coding rate

Type of TrCH Coding scheme

BCH

Coding rate

Convolutional coding

1/3

Turbo coding

DCH FACH DSCH USCH

RACH

TCH

1/3

1/2

Non coding


WCDMA

Convolutional coding Structure of (2,1,8)


WCDMA

Convolutional coding :Structure of (3,1,8)


WCDMA

xk

xk

zk

Turbo codeinternal interleaver

x’k

z’k

D

DDD

DD

Input

OutputInput

Output

x’k

1st constituent encoder

2nd constituent encoder

Structure of rate 1/3 Turbo coder (dotted lines apply for trellis termination only)

1

0

( )( ) [1, ]

( )

DG D

D

gg

2 3

0

3

1

1

1

g D Dg D D


CDMA2000

Output 0G0 = 557 (octal)

InputD D D D D D D D






(a) Rate 1/2 convolutional coder

(b) Rate 1/3 convolutional coder

Convolutional coding :Structure of(2,1,8) and (3,1,8)


CDMA2000

I NPUT OUTPUT

+ + + + +++ ++

++ +

++

++

++

++

Convolutional coding :Structure of (4,1,8)


CDMA2000 : Turbo coding

++

++

+

+

+I NPUT

I nterLeaver

X

Y1

Y2

++

++

+

+

+

X'Y1'

Y2'

OUTPUT

Del ete

and

repeat


TD-SCDMA

Type of TrCH Coding scheme

BCH

Coding rate

Convolutional coding1/2

1/3

Turbo codingDCH FACHDSCH USCH

RACH

TCH

1/3

1/3

1/3

1/2

1/2

Non coding

Usage of channel coding scheme and coding rate


TD-SCDMA








(a) Rate 1/2 convolutional coder

(b) Rate 1/3 convolutional coder

Convolutional coding (2,1,8) and (3,1,8)


TD-SCDMA :Turbo

1

0

( )( ) [1, ]

( )

DG D

D

gg

2 3

0

3

1

1

1

g D Dg D D

xk

xk

zk

Turbo codeinternal interleaver

x’k

z’k

D

DDD

DD

Input

OutputInput

Output

x’k

1st constituent encoder

2nd constituent encoder


Outline



AMC: Adaptive Modulation and Coding

Adaptive Modulation and Coding (AMC) is an alternative link adaptation method in 3G mobile wireless communication. AMC provides the flexibility to match the modulation-coding scheme to the average channel conditions for each user. With AMC, the power of the transmitted signal is held constant over a frame interval, and the modulation and coding format is changed to match the current received signal quality or channel conditions.


“Adaptive” --- A Concept

What is adaptive? Why adaptive?

Nonadaptive: worst-case channel conditions, inefficient utilization of the channel.

Adaptive: increase average throughput, reduce required transmit power, sufficient use of the channel capacity

How to adaptive?favorable channel conditions : higher data rates or lower

powerchannel degrades : reducing the data rate or increasing

power


Introduction

First proposed by J. F. Hayes in 1968 “Adaptive feedback communications”, IEEE Trans.

Commun. Technol. Vol. 16, Issue 1, pp. 29-34Hardware constraintLack of good channel estimation techniquesPoint-to-point radio links without feedback

Has already been used in cellular systems GSM,EDGE,GPRS,cdma2000,WCDMA etc.


Introduction

Main idea of adaptive transmission: transmission schemes are adapted according to

the estimated channel condition that sent back to the transmitter


Introduction

Purpose:Maintain an acceptable bit error rate (transmission

quality)Make a more efficient use of the channel capacity

Wired Networks

Low Rate

BaseStation

ClientRadio Tower

Server

Client

Client

Radio Tower

Interference


Introduction

Several practical constraints:Channel estimation

• Fast, slow

Pr/Pt

d=vt

PrPt

d=vt

v Very slow

SlowFast


Introduction

Several practical constraints:Channel estimation

• Fast, slow

Feed back delay• voice or video

Hardware constraints • how often the transmitter can change its rate

and/or power


Some definitions

: instantaneous received signal-to-noise ratio:average received SNR

: fading distribution of

: transmit power

: average transmit signal power: the number of points in each signal constellation

)(p

)(S

S

M


System Model

0e1][/][ˆ][ iii

0f


System Model

Transmission parameters that can be adapted (according to ):data rate (constellation size)

Coding rateerror probabilitytransmitted power

or any combination of these parameters


Variable Coding Techniques

Different channel codes are used to provide different coding gain to the transmitted bits. particularly useful when modulation fixed

For example:

is small A stronger error correction code

is large A weaker code or no coding


Variable Coding Techniques

Constraints:Channel remain roughly constant over the

block length of constraint length of the code

Implementation:Multiplexing codes with different error

correction capabilitiesRCPC codes (Rate-compatible punctured

convolution codes)


Examples

HSDPA


Our Work---AMC with LDPC Codes

The BER-CSNR relationship of LDPC codes

For a target BER

and are all constants

cbaeBER

)1(

1)(

)(

nc

nn b

BERan )1)

1ln((

1 /1

0

, ,a b c , ,n n na b c


Simulation results

Simulation parameters

nCode Rate

Information Bits

Modulation Scheme

Spectral Efficiency

1

2

3

4

5

1/2

2/3

3/4

4/5

5/6

252

504

756

1008

1260

4-QAM

8-QAM

16-QAM

32-QAM

64-QAM

1

2

3

4

5


Simulation results

threshold selection according to performances of individual schemes under AWGN channel (target BER=10-4)


Simulation results

Performance of adaptive and non-adaptive LDPC codes under Rican fading channel (K=5,assuming ideal channel estimation)


Simulation results

BER performance of adaptive LDPC under constant channel estimation error (CEE)


Simulation results

Spectral efficiency of adaptive LDPC codes under Rican fading channel under different channel estimation error

wireless mobile communication and transmission lab. chapter 8 application of error control coding

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