10 january,2002seminar of master thesis1 helsinki university of technology department of electrical...

10 January,2002 Seminar of Master Thesis 1

Helsinki University of Technology

Department of Electrical and Communication Engineering

WCDMA Simulator with Smart Antennas

Hong Zhang

Communication laboratory

Supervisor: Professor Seppo J. Halme

Instructor: M. Sc. Adrian Boukalov




Outline

1. Background

2. Different approach in WCDMA system modelling

3. Spreading in WCDMA

4. RAKE Receiver and Multiuser Detection

5. Smart Antenna in WCDMA

6. Simulation Results

7. Conclusion




The goal of 3Gto provide a wide variety of communication

services and high speed data access.

The increasing demand of high

capacity

WCDMAradio access technology for 3G

To provide high capacity

Spreading Smart antenna RAKE receiver Multiuser detection

Simulation

1. Background

technique

tool




2. Different approach in WCDMA system modelling (1)

CDMA System Modelling

Synchronous CDMA

Asynchronous CDMA

Modeling with single path

Modeling with multipath

Modeling with smart antenna

Modeling with AWGN channel

Modeling with channel fading

With linear algebra knowledge

com

plex

ity




DOA

The tapped delay line model

T

β0

T

β 1

T

β N-1

Linear time-variant system β( ,t)vmax max<<1

Quasi-stationary βt()Uncorrelated scatters

GWSSUS

Sampled

βi(t)( - i )

Tapped delay line

Ws max<<1

βj(t) ( - jT)

Narrowband model β0(t)

1

0

N

j

i

Ray tracing model

where βj (t) is the complex amplitude, j is path delay and θj is

Direction Of Arrival, a( θ - θj) is the steering vector

GWSSUS: Gaussian Wide Sense Stationary Uncorrelated Scatters

DOA: Direction Of Arrival

h (t, , θ) = βj (t)( - j ) ( θ - θj)

1

0

N

j

2. Different approach in WCDMA system modelling (2): Mobile radio channel

h (t, , θ) = βj (t)( - j ) a( θ - θj)

1

0

N

j

Multiple antennas in the receiver




xkdkbk

spreader

PN code

source of information

encoder/interleaver

transmitterfilter D/A

IF-RFupconverter

Block diagram of the mobile transmitter for user k

xk(t)

Block diagram of the base station receiver

receiver front – end

multiuserdetector

unit

sink K

sink 1

Despreader unit 1

PN code

Despreader unit K

PN code

yMF

r (t)

b

2. Different approach in WCDMA system modelling (3):

the fundamental structure




Discrete time model base band uplink model for asynchronous CDMA system

over a mobile radio channel

n

r

d1(i)s1(i)

u1 p c1,1(i) ... c1,M(i)

d2(i)s2(i) u1 p c2,1(i) ... c2,M(i)

dK(i)sK(i) u1 p cK,1(i) ... cK,M(i)

.

.

.

.

.

.

.

.

.

The output after matched filtering and correlating

The received signal

2. Different approach in WCDMA system modelling (4): Discrete time base band uplink model for asynchronous CDMA




The received signal

The output after matched filtering and correlating

The phase difference of the received signal between adjacent antenna elements The ULA with the direction of arrival

(α, φ) indicated

d B

φ

θ

waveform

z

x

y

αB-1

1

D’

2. Different approach in WCDMA system modelling (5): Discrete time base band uplink model for asynchronous CDMA with smart antenna




3. Spreading in WCDMA (1)

an an-1 an-2 an-r

c1 c2 c3 cr

an = c1 an-1 + c2 an-1 + ... + cr an-

Linear shift register

• Pseudo Random (PN) sequence: a bit stream of ‘1’s and ‘0’s occurring randomly, or almost randomly, with some unique properties.




Spreading: to multiply the input information bits by a PN code and get processing gain, the chip level signal’s bandwidth is much wider than that of input information bits. It maintains the orthogonality among different physical channels of each user.

Scrambling: to separate the signals from the different users. It doesn’t change the signal bandwidth. Each user has a unique scrambling code in the system.

• Uplink spreading and modulation

bit rate chip rate

P(t)

Channelization codes (Walsh/OVSF)

(Cd )DPDCH

j

Channelization codes

(Walsh/OVSF) (Cc)

DPCCH

Scramblingcodes

(Csc)

P(t)

cos ( ωt)

sin ( ωt)

(Gold)

chip rate

WCDMAan interference limited system

Selecting codes high autocorrelation low cross correlation

Suppressing interference

3. Spreading in WCDMA (2) : Spreading and scrambling at the uplink




C 1,1 = ( 1 )

C 2,2 = ( 1 , 1 )

C 2,1 = ( 1 , 1 )

C 4, 2 = ( 1 , 1 , -1 , -1 )

C 4,1 = ( 1 , 1 , 1 , 1 )

C 4, 3 = ( 1 , -1 , 1 , -1 )

C 4,4 = ( 1 , -1, -1, 1 )

SF=1 SF=2 SF=4

• Walsh-Hadamard code Purpose: spreading Generation: code tree

• Gold code

Purpose: scrambling

Generation: modulo-2 sum 2 m-sequences

3. Spreading in WCDMA (3) : Walsh-Hadamard code and Gold code




4. RAKE Receiver and Multiuser Detection (1): RAKE receiver

r

ck,1(i)*

Correlator

sk(i)*

Finger 1

ck,M(i)*

Correlator

sk(i)*

Finger M

y

W

1W

1

T

o()

T

o()

• Combining methods Selection Combining Maximal Ratio Combining (MRC)

Equal Gain Combining (EGC)

RAKE receiver: to collect the signal energy from different multipath components and coherently combine the signal

Output :

SNR

Optimal for single user system




Optimal DetectorWCDMA

Multiple access

MAI

MUDdesign and analysis the

digital demodulation in the presence of

MAI

User 1 RAKE

User 2 RAKE

User K RAKE Vite

rbi A

lgor

ithm

r(t)

)(1 id

)(2 id

)(idK

Sub Optimal Detector

LMMSE: Linear Minimum Mean Square ErrorMUD: multiuser detectionMAI: multiple access interference

High complex

4. RAKE Receiver and Multiuser Detection (2): Multiuser Detection




Decorrelating Detector

SubOptimal Detector

Decorrelating detector for 2 synchronous users

r(t)s1(t)

s2(t)

y1

y2

+-

-+

T

0

)(1 id

)(2 id

T

0

T

0

(synchronous)

(asynchronous)

LMMSE

LMMSE: Linear Minimum Mean Square ErrorMUD: multiuser detectionMAI: multiple access interference

(synchronous)

(asynchronous)

Noise

4. RAKE Receiver and Multiuser Detection (3): Multiuser Detection

Varying channel

Adaptive MMSE algorithm-RLS algorithm with adaptive memory




5. Smart Antenna in WCDMA (1)

Desired signal

Interfering signal

• switched beam antenna array

Smart Antenna consists of antenna array, combined with signal processing in space (or time) domain

Desired signal

Interfering signal

• adaptive antenna array Type

Broad-band beam-former structure

Reference signal

Weight control

Error signal

y(t)

Tτ1 (φi,θi)r1

T

w11 w12 w1M

TτB (φi,θi)rB

T

wB1 wB2 wBM

Steering Delay

-

+




Conventional Beamforming

Statistically Optimum

Beamforming

Adaptive Beamforming

RLS algorithm with adaptive memory

wc = (1 /B ) s

MMSE w = R-1 p

Max SNR Rn-1Rs w = λmax w

LCMV w = R-1c[cHR-1c]-1g

λ(k)= λ(k-1)+α Re[)1(̂kHr(k) ζ *(k)]]

MMSE: mimimize mean square errorLCMV: Linearly Constrained Minimum Variance RLS: recursive least squares

5. Smart Antenna in WCDMA (2): Beamforming schemes




6. Simulation (1)

• Simulation block diagram of transmitter in WCDMA uplink

spreading scrambling

bit rate

chip rate

chip rate

Modulation(BPSK)

Pulse shaping filter

Channelh(1)(t)

dK(i)( user K)

MAI

d2(i) ( user 2)

Modulation(BPSK)


Channelh(2)(t)

Modulation(BPSK)


Channelh(K)(t)

d1(i) ( user 1)


6. Simulation (2)

• Simulation block diagram of 2- D RAKE receiver in uplink WCDMA

User K

User 1 Spatial processing Temporal processing (RAKE)

Multiuser

Detection

W1,M

W1,2

n(t)

●

●

●●

●

●

●

●

W1,1

●

●●

●*

1(t-τM)

*1(t-τ2)

*1(t-τ1)

WK,M

WK,2●

●

●

●

●

WK,1

●

●●

●*

1(t-τM)

*1(t-τ2)

*K(t-τ1)

T

o()

T

o()

T

o()

T

o()

T

o()

T

o()

)(1 id

)(idK



c~

c~




6. Simulation (3)

• Channel: ray tracing channel model

The simulation area : the campus area of Dresden University of Technology.

Simulation area

BTS MS location




6. Simulation Results(4)

• Assume all the users randomly access the channel, and the PN code of each user is acquired and synchronized perfectly in the base station.

• Assume the number of fingers in RAKE receiver equal to the number of multipath components.

• The channel parameters are updated symbol by symbol, i.e. channel varies with time.

The system performance of 1-D RAKE and conventional

matched filter receiver for single user

System performance of 1- D RAKE receiver with Decorrelating Detector

and linear MMSE

DD: Decorrelating Detector LMMSESA: smart antenna for spatial processing PG: Processing GainMUD: Multiuser Detection


0 10 20 30 40 50 60 70 80

10-2

10-1

100

System performance

SNR (dB)

BE

R

ConventionalRakeSA RAKESA RAKE adaptive MUD(RLS)



6. Simulation Results(5)

3 antenna elements3 active users

2 antenna elements3 active users

The system performance of 1-D RAKE with different

Processing Gain

The system performance of 1-D RAKE with spreading by Walsh codes and scrambling by Gold codes spreading and scrambling by random codes

The system performance of 2-RAKE receiver with RLS algorithm with adaptive memory for spatial processing and MUD

DD: Decorrelating Detector LMMSESA: smart antenna for spatial processing PG: Processing GainMUD: Multiuser Detection




7. Conclusion

• The simulation results have shown that spreading, RAKE receiver, multiuser detection and smart antenna are very important techniques to improve WCDMA system performance and increase system capacity.

10 january,2002seminar of master thesis1 helsinki university of technology department of electrical...

Documents

wcdma system

communication engineering

smart antenna modeling

multipath modeling

conclusion slide

awgn channel modeling

single path modeling

adrian boukalov slide