spatial channel model

8/2/2019 Spatial Channel Model

http://slidepdf.com/reader/full/spatial-channel-model 1/39



NOT for distribution, confidential

2

Channel Models for Multiple Antennas

The spatial properties of channels are extremelyimportant in determining the performance of multipleantenna systems

Diversity scheme may correspond to its own channel model

Need to consider Time delay spread

Angular spread

Adaptive array antenna geometries

Angular spread depends on

Local scattering environment Antenna heights

Time variability of spatial channel is the function of UEspeed. (movement)




3

Properties of Spatial Correlation

Lower correlation with Larger angular spread

Larger element spacing

To get low correlation UE: 0.2 wavelength due to the larger angular spread BS: 40 wavelength due to the small angular spread

Assumptions: Long-term properties of the channel remain

unchanged over time (time-invariant) It is a slow varying effect similar to shadow fading

Independence between different taps




4

SCM Generation Method

Spatially correlated multiple channels can begenerated by the linear transformation of thesame number of uncorrelated channels

(t)gT(t)h

HTTR Correlation matrix:

(t)g

(t)g

(t)g

(t)g

L

2

1

Uncorrelated channels:




5

Block Diagram for SCM Generation

Multiple

channelgeneration

Linear

transformationwith T

)(1 t g)(1 t h

)(t g L

)(2 t g

)(t h L

)(2

t h

Matrix squareroot

computation

T

H T T R

Spatial correlationcoefficients

(t)gt(t)hL

1 j

jiji




6

Alternative Implementationfor Rx Diversity Simulations

When spatial covariance matrices are equal foreach tap

Equivalent simulation method without changethe channel impulse responses by transformationof

Received signal before AWGN

Antenna weightwTv and

r

r

r

T

s

s

s

L

2

1

L

2

1




7

Examples of Spatial Correlation Matrix

Spatial correlation matrix for 4 antenna case

Spatially uncorrelated channels: a=b=c=0 Recommended correlation coefficients

[TSGR1#17(00)1358]

1*a*b*c

a1*a*b

ba1*a

cba1

R




8

Recommended Correlation Parameters[TSGR1#17(00)1358]

Environment ParametersRecommended path

model Angular spread

Macro cell

(Rural area)

a=0.97 exp(-0.8 j)

b=0.94 exp(-1.6 j)c=0.88 exp(-2.4 j)

1-path Rayleigh

Vehicular A

10° AS

15° AoA

Micro cell

(Urban area)

a=0.7 exp(-2.2 j)

b=0.1 exp(-1.2 j)

c=0.2 exp(-3.0 j)

Pedestrian A 45° AS

60° AoA

Pico cell oruncorrelated

a, b, c = 0 Pedestrian A Large angular

spread




9

What Next?

Rx or Tx Diversity schemes have been simulated withthose correlation matrices.

Is it Reliable? Reasonable? Enough?

Need verification of the recommended SCM

Need some basics of array signal processing

Rx signal model to array antenna

Steering vector Power Spectrum Density (PSD)

Eigenbeam pattern




10

Received Signal Model

(t)nθas(t)

(t)nαs(t)

(t)nαs(t)

(t)nαs(t)

(t)ns(t)

(t)r

L1-L

32

21

1

Steering vector is the function of AOA dependent on the antenna geometry

A o

An

0

Node B

s(t)

Rx signal with coherent assumption

1-L

1

α

α

1

θa




11

Steering Vector of Uniform Linear Array

1

2

1

1

L

L

a

sin~

2exp d j

Phase Differencebetween twoadjacent antenna

Steering vector of ULA:

Plane wave

)sin( d

Boresight

AoA




12

Discrete Uniform Distribution Model

A o

A

n

0

Node B

UE

(t)nθa1Q

1s(t)(t)r

Q

0q

q

Angle of sub-paths:

HQ

0q

qq θaθa1)(Q

1R

σ2

1

Q

qθθq

Correlation Matrix:

Rx Signal:




13

More Basic Definitions

θaRθaθPH

1

Power Spectrum Density

θawwθa

wθaθP

HH

2H

2

Beam pattern of antenna weight

H

LLL

H

222

H

111 wwλ wwλ wwλ R

Eigenvalue decomposition




14

-80 -60 -40 -20 0 20 40 60 80-20

-10

0

10Angular PSD of correlation matrix

Angle (degree)

G a i n ( d B )

-80 -60 -40 -20 0 20 40 60 80-30

-20

-10

0Dominant Eigenbeam Pattern

Angle (degree)

G a i n ( d B )

PSD of Macro Cell Model: 70 AoA, 10 AS

Long-term average power

profile according toangle

Beam pattern of thedominant eigenvector

Dominant eigenvector isassociated with 99.9%power

AoA is around 15°

AS = 10°




15

-50 0 50-40

-30

-20

-10

0

Angle (degree)

G a i n ( d B )

Dominent Eigenbeam Pattern

-50 0 50-40

-30

-20

-10

0

Angle (degree)

G a i n ( d B )

2nd Eigenbeam Pattern

-50 0 50-40

-30

-20

-10

0

Angle (degree)

G a i n

( d B )

3rd Eigenbeam Pattern

-50 0 50-40

-30

-20

-10

0

Angle (degree)

G a i n

( d B )

4th Eigenbeam Pattern

Eigenbeam Patterns of Macro Model

0 %0 %

99.9% 0.1%




16

-80 -60 -40 -20 0 20 40 60 80-30

-20

-10

0

10Angular PSD of correlation matrix

Angle (degree)

G a i n ( d B )

-80 -60 -40 -20 0 20 40 60 80-40

-30

-20

-10

0Angular PSD of dominant eigenvector

Angle (degree)

G a i n ( d

B )

PSD of Micro Cell Model: 60 AoA, 45 AS

Dominant eigenvector isassociated with 57%of total power

60 AoA

45 AS




17

-50 0 50-40

-30

-20

-10

0

Angle (degree)

G a i n ( d B )

Dominent Eigenbeam Pattern

-50 0 50-40

-30

-20

-10

0

Angle (degree)

G a i n ( d B )

2nd Eigenbeam Pattern

-50 0 50-40

-30

-20

-10

0

Angle (degree)

G a i n ( d

B )

3rd Eigenbeam Pattern

-50 0 50-40

-30

-20

-10

0

Angle (degree)

G a i n ( d

B )

4th Eigenbeam Pattern

Eigenbeam Patterns of Micro Cell

0.4 %3.7 %

57.2% 38.7%




18

Need Common Correlation Model

Very limited simulation environments can beconsidered

Eigenbeamformer scheme has adopted this spatialchannel model

Uniformly distributed power on an angular region

Common & more reliable simulation spatial

channel model is required Need specific descriptions of more channel

parameters, AOA, PAS, AS, etc




19

Spatial Channel Model by AHG

Text description: SCM-077 11/2002 Recommended to use MIMO physical layer channel

model proposed

SCM AHG (AH-62) from 3GPP & 3GPP2

Develop and specify parameters and methodsassociated with Link level spatial channel model

For calibration only

System level spatial channel model Define physical parameters and system evaluation

methodology




20

Link level channel model

Developed and specified by 3GPP-3GPP2 SCM AH

Only for calibration purposes

Reflect only one snapshot of the channel behavior

Do not account for system attributes such asscheduling and HARQ

Only for comparison of performance results fromdifferent implementation of a given algorithm

Status: 95% completed

Distribution is not defined yet




21

System level channel model

Required for the final algorithm comparison Define the methodology for generating the

spatial channel coefficients between BS and MS

95% completed Will not be covered here but later




22

Terminologies MS = UE = terminal

= subscriber unit

BS = Node-B = BTS

AS = angle spread

= azimuth spread

Path = Ray Path component

= Sub-ray

PAS = power azimuthspectrum

DoT = direction of travel

AoA = angle of arrival

AoD = angle of departure

PDP = power delay profile

A o

A

n

0 BS

UE

D o T




23

Parameters of Link Level SCM

Model Case I Case II Case III Case IV

3GPP Case B Case C Case D Case A

3GPP2 Model A, D, E Model C Model B Model F

PDP Mod. Pedestrian A Vehicular A Pedestrian B Single path

Speed (Km/h)1) 3

2) 30, 1203, 30, 120 3, 30, 120 3

# of paths1) 4 + 1 (LOS on, K=6 dB)

2) 4 (LOS off)6 6 1

Relative pathpower (dB)

& Delay (ns)

LOS on

0.0

-6.51

-16.21

-25.71

-29.31

LOS off

–Inf

0.0

-9.7

-19.2

-22.8

0

0

110

190

410

0.0

-1.0

-9.0

-10.0

-15.0

-20.0

0

310

710

1090

1730

2510

0.0

-0.9

-4.9

-8.0

-7.8

-23.9

0

200

800

1200

2300

3700

0 0

Multipath fading propagation conditions




24

Parameters of Link Level SCM…


Topology Reference: ULA with 0.5, 4, 10 spacing N/A

PASLaplacian distribution with

RMS angle spread of 2 or 5 degrees per path

depending on AoA/AoD

N/A

AoD/AoA

(degrees)

50 for 2 RMS AS per path

20 for 5 RMS AS per pathN/A

Antenna gainpattern

3 or 6 sector antenna pattern

(For diversity oriented applications rather than beamforming applications)

Spatial parameters for NodeB




25

Parameters of Link Level SCM…


Topology Reference 0.5 N/A

PAS

1) LOS on: Fixed AoA forLOS component, remainingpower has 360 degree

uniform PAS. ( RMS anglespread of 104 degrees)

2) LOS off: Laplaciandistribution with RMS anglespread of 35 degrees perpath

Laplacian distributionwith RMS anglespread of 35 degreesper path

OR

360 degree uniformPAS ( RMS anglespread of 104degrees)

Laplacian distributionwith RMS anglespread of 35 degreesper path

N/A

DoT

(degrees) 0 22.5 -22.5 N/A

AoA

(degrees)

22.5 (LOS component)

67.5 (all other paths)67.5 (all paths)

22.5 (odd paths)

-67.5 (even paths)N/A

Antenna gainpattern

Omni directional with -1 dBi gain

Spatial parameters for UE




26

Assumptions of Link Level SCM

Spatial channel parameters per path Each resolvable path is characterized by spatial

channel parameters: AS, AoA, PAS

All paths are assumed independent

Array Topologies

Allow any type of antenna configuration, but must be

shared to reproduce and verify the results ULA with element spacing of 0.5, 4, 10 wavelengths




27

Antenna Gain Patterns

UE: -1 dBi gain omni-direction Node B uplink/downlink

Only for diversity oriented implementations (large spacing)

Need different antenna patterns for beamforming applications

3 sector cell Bandwidth 70°, Maximum attenuation 20 dB, 14 dBi gain

6 sector cell

Bandwidth 35°, Maximum attenuation 23 dB, 17 dBi gain

Sector antenna formula in dB scale

180θ180,A,θ

θ12-minθA m

3dB

O f di ib i fid i l




28

Sector Antenna Patterns at NodeB

-120 -100 -80 -60 -40 -20 0 20 40 60 80 100 120-25

-20

-15

-10

-5

0Antenna Pattern for 3 sector cell

Azimuth in Degrees

G a i n i n d B

BW = 70 degreeBW = 70 degree

maximum attenuation (Am)

3 sector antenna pattern

NOT f di t ib ti fid ti l




29

Sector Antenna Patterns at NodeB…

-120 -100 -80 -60 -40 -20 0 20 40 60 80 100 120-25

-20

-15

-10

-5

0Antenna Pattern for 6 sector cell

Azimuth in Degrees

G a i n i n d B

BW = 35 degreeBW = 35 degree

maximum attenuation (Am)

6 sector antenna pattern





30

Average Received Power

θGσ

θθ2expNθP 0

dθθPNπ

π

1

0

/10θA10θG

Laplacian distributed PAS

Normalization factor

Gain pattern in linear scale

θ Angle of Arrival

θEθEσ22 RMS angle spread





31

Average Received Power at NodeB

-50 -40 -30 -20 -10 0 10 20 30 40 500

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2Avaerage received power

Angle (degree)

P A S

v a l u e P ( )

3 sectored antenna with AoA = 20 and RMS AS = 5





32

Average Received Power at UE

Laplacian distributed PAS with omni-directional gain 1θG

σ

θθ2expNθP 0

NOT for distribution confidential




33

Average Received Power at UE…

22.5 AoA & 35 RMS AS

-150 -100 -50 0 50 100 1500

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0.02Avaerage received power

Angle (degree)

P A S

v a l u e P ( )





34

Average Received Power at UE…

22.5 AoA & 104 RMS AS (uniform over 360 degree PAS)

-150 -100 -50 0 50 100 1500

1

2

3

4

5

6

7

8x 10

-3 Avaerage received power

Angle (degree)

P A S

v a l u e P ( )





35

Doppler Spectrum at UE

Dependent on DoT

PAS

AoA

A o

A

n

0 BS

UE

D o T





36

Generation of link level channel model

Average received power Angle theta represents path components

Its distribution is TBD Uniformly distribution over [-180 180] degrees

Channel implementation techniques Correlation based

Ray based

Details are TBD Reference correlation values are provided

Nokia to provide formulas for computing correlationmatrices





37

Future Plan

Link-level SCM generation and verification MatLab, SPW, etc

Continual study of system-level models

Using these models for performance testing invarious development projects (TDD, FDD, EV-DV,

TD-SCDMA)





References

Old 3GPP Model: TSGR1#14(00)0867

TSGR1#15(00)1067

TSGR1#16(00)1187

TSGR1#17(00)1358 Tx Div Model:

TSGR1#26(02)

0765, 770

TSGR1#29(02)1139,1419,1440

1441 (TR25.869)

MIMO Model: TSGR1#22(01)1132

TSGR1#22(01)1136

TSGR1#23(01)1179 TSGR1(02)0141

SCM-077,November 2002

by 3GPP-3GPP2

spatial channel model

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