College of Engineering Capacity Allocation in Multi-cell UMTS Networks for Different Spreading Factors with Perfect and Imperfect Power Control Robert.

College of Engineering

Capacity Allocation in Multi-cell UMTS

Networks for Different Spreading Factors with Perfect and Imperfect

Power Control

Capacity Allocation in Multi-cell UMTS

Networks for Different Spreading Factors with Perfect and Imperfect

Power ControlRobert Akl, D.Sc.

Son Nguyen, M.S.

Department of Computer Science and Engineering

Robert Akl, D.Sc.

Son Nguyen, M.S.

Department of Computer Science and Engineering

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OutlineOutline

• User and Interference Model

• WCDMA Capacity with Perfect Power Control

• WCDMA Capacity with Imperfect Power Control

• Spreading Factors

• Numerical Results

• Conclusions

• User and Interference Model

• WCDMA Capacity with Perfect Power Control

• WCDMA Capacity with Imperfect Power Control

• Spreading Factors

• Numerical Results

• Conclusions

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CDMA with One Class of UsersCDMA with One Class of Users

Cell j

Cell i

jr

ir

10

2

, 10 ,

, /E

jm

jjji mCj ji i

r x y ndA x y

Ar x yI

2 ( , ) ( , )

( , )

ms j

ji miC j

nj r x ye dA x y

Aj r x yI

jiI Relative average interference at cell

i caused by nj users in cell j

dAln(10)

10

s

where

is the standard deviation of the attenuation for the shadow fading

m is the path loss exponent

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WCDMA with Multiple Classes of Users

WCDMA with Multiple Classes of Users

2( )

, ,

( , )( , ) ( , )

( , )

s

j

mj

ji g g g j g mj iC

r x yeI S v n w x y dA x y

A r x y

is the user distribution density at (x,y)

w(x,y)

• Inter-cell Interference at cell i caused by nj users in cell j of class g

• Inter-cell Interference at cell i caused by nj users in cell j of class g

2( )

,

( , )( , ) ( , ).

( , )

s

j

mj

ji g mj iC

r x yew x y dA x y

A r x y

is per-user (with service g) relative inter-cell interference factor from cell j to BS i

,ji g

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Total Inter-cell Interference Density in WCDMA

Total Inter-cell Interference Density in WCDMA

inter, ,

1, 1

1 M G

g g g j g ji gj j i g

I S nW

M is the total number of cells in the network

G total number of servicesW is the bandwidth of the

system

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Model User Density with 2D Gaussian Distribution

Model User Density with 2D Gaussian Distribution

2 21 2

1 2

1 1

2 2

1 2

( , )2

x y

w x y e e

own,

1

1 G

g g g i gg

I S nW

is the total intra-cell interference density caused by all users in cell i

• “means” is a user density normalizing parameter• “variances” of the distribution for every cell

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Signal-to-Noise Density in WCDMASignal-to-Noise Density in WCDMA

is the thermal noise density,

is the bit rate for service g

0N

Rg

own inter0 ,0

g

gb

g gi gi i

S

RESI

N I IW

is the minimum signal-to-noise ratio required

0 , , ,1 1, 1

g

gg G M G

gi g g j g g ji g g

g j j i g

S

R

SN n n

W

g

wherewhere

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Simultaneous Users in WCDMA Must Satisfy the Following Inequality Constraints

Simultaneous Users in WCDMA Must Satisfy the Following Inequality Constraints

( )

0

1 ggeff

g g g

RWc

R S N

is the minimum signal-to-noise ratio

g

is the maximum signal powergS

the number of users in BS i for given service g

,ni g

( ), , ,

1 1, 1

G M Gg

i g g j g g ji g g effg j j i g

n n c

1, 2, ,( , , , )g g M Gn n n1, ,g G

The capacity in a WCDMA network is defined as the maximumThe capacity in a WCDMA network is defined as the maximumnumber of simultaneous users for all servicesnumber of simultaneous users for all services

. This is for perfect power control (PPC).. This is for perfect power control (PPC).

wherewhere

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Imperfect Power ControlImperfect Power Control

• Transmitted signals between BSs and MSs are subject to multi-path propagation conditions

• The received signals vary according to a log-normal distribution with a standard deviation on the order of 1.5 to 2.5 dB. Thus in each cell for every user with service needs to be replaced

• Transmitted signals between BSs and MSs are subject to multi-path propagation conditions

• The received signals vary according to a log-normal distribution with a standard deviation on the order of 1.5 to 2.5 dB. Thus in each cell for every user with service needs to be replaced

0 ,

bEI i g

2, , ( )

0 0

( ) ( )cb o b b i b

i,g

E EE e

I I

, ,( ) ( )b i b i,g b o bE E

,( )b i bE ig

2( )2

( )( )

_ c

geffg

eff IPC

cc

e

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Relationship between Spreading and Scrambling

Relationship between Spreading and Scrambling

• Channelization codes: separate communication from a single source

• Scrambling codes: separate MSs and BSs from each other

• Channelization codes: separate communication from a single source

• Scrambling codes: separate MSs and BSs from each other

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Main differences between WCDMA and IS-95 air interfaces

Main differences between WCDMA and IS-95 air interfaces

Channelization code Scrambling code

Usage Uplink: Separation of physical data (DPDCH) and control channels (DPCCH) from same MS

Downlink: Separation of downlink connections to different MSs within one cell.

Uplink: Separation of MSs

Downlink: Separation of sectors (cells)

Length Uplink: 4-256 chips same as SF

Downlink 4-512 chips same as SF

Uplink: 10 ms = 38400 chips

Downlink: 10 ms = 38400 chips

Number of codes

Number of codes under one scrambling code = spreading factor

Uplink: Several millions

Downlink: 512

Code family Orthogonal Variable Spreading Factor

Long 10 ms code: Gold Code

Short code: Extended S(2) code family

Spreading Yes, increases transmission bandwidth

No, does not affect transmission bandwidth

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Spreading FactorSpreading Factor

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Orthogonal Variable Spreading Factor (OVSF) codes

Orthogonal Variable Spreading Factor (OVSF) codes

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SimulationsSimulations

• Network configuration

• COST-231 propagation model

• Carrier frequency = 1800 MHz

• Average base station height = 30 meters

• Average mobile height = 1.5 meters

• Path loss coefficient, m = 4

• Shadow fading standard deviation, σs = 6 dB

• Bit energy to interference ratio threshold, τ = 9.2 dB

• Activity factor, v = 0.375

• Processing gain, W/R = 6.02 dB, 12.04 dB, 18.06 dB, and 24.08 dB for Spreading Factors equal to 4, 16, 64, and 256.

• Network configuration

• COST-231 propagation model

• Carrier frequency = 1800 MHz

• Average base station height = 30 meters

• Average mobile height = 1.5 meters

• Path loss coefficient, m = 4

• Shadow fading standard deviation, σs = 6 dB

• Bit energy to interference ratio threshold, τ = 9.2 dB

• Activity factor, v = 0.375

• Processing gain, W/R = 6.02 dB, 12.04 dB, 18.06 dB, and 24.08 dB for Spreading Factors equal to 4, 16, 64, and 256.

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Numerical ResultsNumerical Results

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Numerical ResultsNumerical Results

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Numerical ResultsNumerical Results

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Numerical ResultsNumerical Results

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Results of Optimized Capacity Calculation

Results of Optimized Capacity Calculation

• The SIR threshold for the received signals is decreased by 0.5 to 1.5 dB due to the imperfect power control.

• As expected, we can have many low rate voice users or fewer data users as the data rate increases.

• The determined parameters of the 2-dimensional Gaussian model matches well with the traditional method for modeling uniform user distribution.

• The SIR threshold for the received signals is decreased by 0.5 to 1.5 dB due to the imperfect power control.

• As expected, we can have many low rate voice users or fewer data users as the data rate increases.

• The determined parameters of the 2-dimensional Gaussian model matches well with the traditional method for modeling uniform user distribution.

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Thank You!!Thank You!!

Questions?Questions?