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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

W CDMA Simulator with Smart Antennas - Aalto · W CDMA Simulator with Smart Antennas Hong Zhang ... RAKE Receiver and Multiuser Detection 5. ... Modeling with multipath

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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

10 January,2002 Seminar of Master Thesis 2

Helsinki University of Technology

Department of Electrical and Communication Engineering

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

10 January,2002 Seminar of Master Thesis 3

Helsinki University of Technology

Department of Electrical and Communication Engineering

The goal of 3Gto provide a wide variety of communication

services and high speed data access.

The increasing demand of highcapacity

WCDMAradio access technology for 3G

To provide high capacity

SpreadingSmart antennaRAKE receiverMultiuser detection

Simulation

1. Background

technique

tool

10 January,2002 Seminar of Master Thesis 4

Helsinki University of Technology

Department of Electrical and Communication Engineering

2. Different approach inWCDMA 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 linearalgebra knowledge

com

plex

ity

10 January,2002 Seminar of Master Thesis 5

Helsinki University of Technology

Department of Electrical and Communication Engineering

DOA

The tapped delay line model

T

0

T

1

T

N-1

Linear time-variant system (τ ,t)vmax τmax<<1

Quasi-stationary t(τ)Uncorrelated scatters

GWSSUS

Sampled

i(t)δ( τ - τi )

Tapped delay line

Ws τmax<<1

j(t) δ( τ - jT)

Narrowband model 0(t)

∑−

=

1

0

N

j

∑i

Ray tracing model

where j (t) is the complex amplitude, τj is path delay and j isDirection Of Arrival, a( - j) is the steering vectorGWSSUS: Gaussian Wide Sense Stationary Uncorrelated ScattersDOA: Direction Of Arrival

h (t, τ, ) = j (t)δ( τ - τj ) δ( - j)∑−

=

1

0

N

j

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

h (t, τ, ) = j (t)δ( τ - τj ) a( - j)∑−

=

1

0

N

j

Multiple antennas in the receiver

10 January,2002 Seminar of Master Thesis 6

Helsinki University of Technology

Department of Electrical and Communication Engineering

xkdkbk

spreader

PN code

source ofinformation

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

receiverfront – end

multiuserdetector

unit

sink K

sink 1

Despreader unit 1

PN code

Despreader unit K

PN code

yMF

r (t)

bM

N

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

10 January,2002 Seminar of Master Thesis 7

Helsinki University of Technology

Department of Electrical and Communication Engineering

Discrete time model base band uplinkmodel 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 matchedfiltering and correlating

✦ The received signal

r = ∑−

=

1

0

L

i∑

=

K

k 1∑

=

M

m 1

)()(ˆ , idic kmk

−− NQiL

mk

iNQ

O

i

O

)1(

, )(s + n=SCd+n

y =C H SH S C d + C H SH n

Where )(ˆ , imks =

− mkMO

ikmk

O

)(ˆ,

τ

τs

)(idk : the ith data symbol transmitted by user k

)(ˆ iks : the zero-padded spreading sequence for symbols generated by user k

)(ˆ , ic mk : the channel coefficients over the mth multipath for the ith symbol generated by user k.

L : the total amount of the data symbol sent by every active userK : the total amount of active users sending data to the BTS

M : the maximum delay spread normalised to sampling intervalM : the amount of resolvable multipath components per user data sequenceC: channel matrixS: the matrix of received spreading waveformn: Additive White Gaussian Noise

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

10 January,2002 Seminar of Master Thesis 8

Helsinki University of Technology

Department of Electrical and Communication Engineering

= λ

θπ cos2 d

✦ The received signal

y = HC0HSH r = HC0

HSH S &0 d + HC0HSH n

✦ The output after matched filteringand correlating

✦ The phase difference of the receivedsignal between adjacent antenna elements The ULA with the direction of arrival

( , ) indicated

d B

waveform

z

x

y

B-1

1

D’

r = S �& 0 d +n

where �LV�WKH�VWHHULQJ�PDWUL[

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

10 January,2002 Seminar of Master Thesis 9

Helsinki University of Technology

Department of Electrical and Communication Engineering

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.

10 January,2002 Seminar of Master Thesis 10

Helsinki University of Technology

Department of Electrical and Communication Engineering

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 ( t)

sin ( t)

(Gold)

chip rate

WCDMAan interference limited system

Selecting codeshigh autocorrelation low cross correlation

Suppressing interference

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

10 January,2002 Seminar of Master Thesis 11

Helsinki University of Technology

Department of Electrical and Communication Engineering

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

10 January,2002 Seminar of Master Thesis 12

Helsinki University of Technology

Department of Electrical and Communication Engineering

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

y = CH SH r

10 January,2002 Seminar of Master Thesis 13

Helsinki University of Technology

Department of Electrical and Communication Engineering

Optimal DetectorWCDMA

Multiple access

MAI

MUDdesign andanalysis the

digitaldemodulation inthe presence of

MAI

User 1 RAKE

User 2 RAKE

User K RAKE Vite

rbi A

lgor

ithm

r(t)

∧)(1 id

∧)(2 id

∧)(idK

MM

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

10 January,2002 Seminar of Master Thesis 14

Helsinki University of Technology

Department of Electrical and Communication Engineering

Decorrelating Detector

SubOptimal Detector

Decorrelating detector for 2 synchronous users

r(t)s1(t)

s2(t)

y1

y2

+-

-+∫

T

0

ρ

∧)(1 id

∧)(2 id

∫T

0

∫T

0

(synchronous)

(asynchronous)

Decd = [RT [1] z + R [0] + R [1] z-1 ]-1 y

Decd = R-1y

LMMSE

LMMSE: Linear MinimumMean Square ErrorMUD: multiuser detectionMAI: multiple accessinterference

(synchronous)

(asynchronous)

Decd = (R+ 2I)-1 y

Decd = (RT [1] z + R [0] + R [1] z -1 + 2I )-1 y

Noise

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

Varying channel

Adaptive MMSE algorithm-RLS algorithm with adaptive memory

J(k) = ∑=

−n

i

in

1

λ (| �N�_2 )

10 January,2002 Seminar of Master Thesis 15

Helsinki University of Technology

Department of Electrical and Communication Engineering

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 arrayType

Broad-band beam-former structure

Reference signal

Weightcontrol

Errorsignal

y(t)

T1 ( i, i)r1

T

w11 w12 w1M

TB ( i, i)rB

T

wB1 wB2 wBM

Steering Delay

-

+

M

y(t) = ∑=

B

n 1

wn rn (t)

10 January,2002 Seminar of Master Thesis 16

Helsinki University of Technology

Department of Electrical and Communication Engineering

ConventionalBeamforming

StatisticallyOptimum

Beamforming

AdaptiveBeamforming

RLS algorithmwith adaptivememory

wc = (1 /B ) s

MMSE w = R-1 p

Max SNR Rn-1Rs w = max w

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

G(k) =)()1()(1

)()1(1

1

krkPkr

krkPH −+

−−

λλ

�N��� �G�N� - w H (k-1) r(k)

w(k)= w (k-1) + G(k) *(k)

P(k) = -1 P(k-1) - -1 G(k) rH (k) P(k-1)

�N� � �N���� �5H> )1(ˆ −kHψ r(k) *(k)]]−+

λλ

S(k) = -1[I - G(k) rH (k)] S(k-1) [I - r (k)GH(k)]+ -1 G(k) GH(k)- -1 P(k)

)(kψ = [I - G(k) rH (k)] )1(ˆ −kHψ + S(k) r(k) *(k)

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

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

10 January,2002 Seminar of Master Thesis 17

Helsinki University of Technology

Department of Electrical and Communication Engineering

6. Simulation (1)

• Simulation block diagram of transmitter in WCDMA uplink

spreading scrambling

bitrate

chiprate

chiprate

Modulation(BPSK)

Pulseshapingfilter

Channelh(1)(t)

dK(i)( user K)

MAI

d2(i)( user 2) Modulation

(BPSK)

Pulseshapingfilter

Channelh(2)(t)

Modulation(BPSK)

Pulseshapingfilter

Channelh(K)(t)

d1(i)( user 1)

10 January,2002 Seminar of Master Thesis 18

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- M)

*1(t- 2)

*1(t- 1)

WK,M

WK,2%

%

%

%

%

WK,1

%

%%

%*1(t- M)

*1(t- 2)

*K(t- 1)

∫T

o()

∫T

o()

∫T

o()

∫T

o()

∫T

o()

∫T

o()

∧)(1 id

∧)(idK

Helsinki University of Technology

Department of Electrical and Communication Engineering

c~

c~

N

M M

M

N

N

10 January,2002 Seminar of Master Thesis 19

Helsinki University of Technology

Department of Electrical and Communication Engineering

6. Simulation (3)

• Channel: ray tracing channel model The simulation area : the campus area of Dresden University of Technology.

Simulation area

BTS MS location

10 January,2002 Seminar of Master Thesis 20

Helsinki University of Technology

Department of Electrical and Communication Engineering

6. Simulation Results(4)

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

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

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

The system performance of1-D RAKE and conventional

matched filter receiver forsingle user

System performance of 1- D RAKEreceiver with Decorrelating Detector

and linear MMSE

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

10 January,2002 Seminar of Master Thesis 21

0 10 20 30 40 50 60 70 80

10-2

10-1

100

Sys tem performance

S NR (dB)

BE

RConventionalRakeSA RAKESA RAKE adaptive MUD(RLS)

Helsinki University of Technology

Department of Electrical and Communication Engineering

6. Simulation Results(5)

3 antenna elements3 active users

2 antenna elements3 active users

The system performance of1-D RAKE with different

Processing Gain

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

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

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

10 January,2002 Seminar of Master Thesis 22

Helsinki University of Technology

Department of Electrical and Communication Engineering

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.