master ceri dimensionnement mobile

7/30/2019 Master CERI Dimensionnement Mobile

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Network engineering formobile networks

Salah Eddine El Ayoubi

Orange Labs

[email protected]

2013


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outline

objective: ensuring QoS in mobile networks

coverage in mobile networks

dimensioning radio interface for capacity

2 Salah Eddine Elayoubi Mobile Network Engineering


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coverage targets

mobile operators have to ensure complete coverage:

minimize white zones

cover villages as well as cities

cover routes


limited power

loss due to propagation


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cellular networks

each base station covers a cell / sector

large cells required to reduce costs, however:

degraded QoS at cell edge: coverage problems

many users served: capacity problems



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What is spectrum ?

f1 f2 f3

30 MHz 300 MHz 3 GHz 30 GHz

radio waves are characterized by their frequency, measured in Hertz (Hz)

spectrum is the continuous aggregation of these frequencies


VHF UHF SHF

the operator buys an amount of frequency from the regulator ofeach country

a set of contiguous frequencies is called a carrier

each operator has a limited number of carriers

each carrier has a limited capacity in terms of number of users thatcan be served, as we will see next


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Operator dilemma

coverage is not the only criterion:

QoS in coverage areas is important

QoS includes:

access rate

good communication probability

throughput


operator target: ensure coverage target and QoS

with lowest costs

operator dilemma:

low cost -> large cells -> more users in each cell -> more

spectrum needed

spectrum is limited and too costly


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example of network deployment

exercise



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Challenges related to spectrum

f1

f2

f3


VHF UHF SHF

30 z 300 z 3 GHz 30 GHz

frequency=speed of light / wavelength

different challenges when using different frequency bands large frequency -> small wavelength -> low penetration of obstacles

low frequency -> large wavelength -> large antennas needed


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Main guidelines when managing spectrum

Frequencies that areFrequencies that areFrequencies that areFrequencies that are

usable for cellularusable for cellularusable for cellularusable for cellular

networking are betweennetworking are betweennetworking are betweennetworking are between

400 MHz and 5 GHz400 MHz and 5 GHz400 MHz and 5 GHz400 MHz and 5 GHz Low frequencies areLow frequencies areLow frequencies areLow frequencies are

used when there is aused when there is aused when there is aused when there is a

need for largeneed for largeneed for largeneed for large

coveragecoveragecoveragecoverage


, . ., . ., . ., . .

areas.areas.areas.areas.

High frequencies areHigh frequencies areHigh frequencies areHigh frequencies are

used when there is aused when there is aused when there is aused when there is a

need for large capacity,need for large capacity,need for large capacity,need for large capacity,

e.g. in urban areas.e.g. in urban areas.e.g. in urban areas.e.g. in urban areas.

FrequencyFrequencyFrequencyFrequency

(MHz)(MHz)(MHz)(MHz)400 1000 5000

Terminal

too big

overage

too smallCoveragefrequencies

Capacityfrequencies


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High demand


Limited resource


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How to share spectrum

f3 f3


f1 f1

f2

f2 f3 f1

f2


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outline



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link budget

link budget objective

maximum distance between a user and its serving base station while guaranteeing

a given quality of service

equipment parameters propagation model cell rangereceived signals SINR

13 Salah Eddine EL AYOUBI June 2010


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equipment parameters

determine gains and losses due to equipments.

antenna gain GA: directivity of antenna amplifies the signal in some directions.


feeder loss LF: due to the cable between amplifier and antenna.

for an emitted power Pmax:

F

Amax

L

GPpoweruseful

=


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propagation model







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use of propagation models

Ptxpathloss

C

pathloss

Ptx

I


propagation models allow to compute:

The received signal power ( coverage maps)

The interfering power ( QoS maps) a propagation model is the first building block of (almost) any radio

planning tool

Serving BS Interfering BS


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path loss models

free space propagation

only valid for line of sight, without multiwithout multiwithout multiwithout multi----pathpathpathpath

22

44

=

=

cDfDPathloss

D


these conditions are not met in cellular networks

statistical models (e.g. Okumura-Hata)

simple models with A & B statistically tunedfor typical environments (urban, etc.)

no geographical data required

useful for dimensioning

( ) 4020withlog][ += BDBAdBPathlosse.g. urban environment

D


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received signals







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received signals

for a user situated at distance d from a base station:

)(dPLL

GP

powerreceivedF

Amax

=


PL(d)=path loss at distance d


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SINR







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interference in the dowlink

interference is received by the mobile

from the base stations:

it depends on the position of the

mobile in the cell cell-edge users are subject to

higher interference because they

are closer to interferers.


observations: the origin of interference is well

defined.

the intensity of this interference

is to be calculated.


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interference in the uplink

interference is received by the base

station from the mobiles in adjacent

cells:

it is independent from theposition of the mobile in the cell.

it depends on the distribution of

mobiles in interfering cells.


observations: the average interference is

uniform for all mobiles.

the position of interferers is

unknown.


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SINR calculations

collisions decrease the Signal to Interference Ratio (SINR):

noiseceinterferenreceived

powerreceivedSINR

+=


a lower SINR means a larger Bit Error Rate (BER):

degraded QoS


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cell range







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maximal cell range

for a good reception, the SINR must be larger than a target:

SINR>SINRtarget

for a given cell range R, calculate the SINR at cell edge:

SINR(R)

for a larger R, SINR degrades as received power becomes

lower compared to noise


the optimal cell range is the largest R so that SINR(R)>SINRtarget

in general, the limiting link for coverage is the uplink as mobiles

have low emitted powers.


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example coverage of a cell

exercise



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outline






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Erlang-like capacity

need to install resources:

that insures a Quality of Service (QoS) for users

example: number of frequency carriers per cell user perceived QoS includes:

blocking rates for real-time calls

-


-

this is called Erlang-like capacity:

reference to mathematician Agner Krarup Erlang

example Erlang-B law.


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Erlang-B law

probability of call loss:

B=blockin rate 5055606570758085

9095

1000.0001 0.001 0.01

c

Erlang tableB


E=traffic intensity C= number of circuits

Each call uses one

circuit 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 805

101520253035

40

85

A simple Erlang calculator can be found at:

http://perso.rd.francetelecom.fr/bonald/Applets/erlang.html

E


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the race for bit rates in mobile networks

Wide Area

Mobility

1995 2000 2005 2012

GSMGPRS 4G?

EDGE UMTS LTEHSPA

+

HSDPA

Mobile TV

HSUPA

Wide Area

Mobility

Mobility

1995 2000 2005

4G?EDGEUMTS LTE

HSPA

+

HSDPA

DVB-x


Short range

Mobility

Data Rate

10kbps 100kbps

Fixed

WLAN

Fix

1Mbps 10Mbps 100Mbps

.

Data Rate

10kbps 100kbps

Fixed

WLAN

Fixed

Wimax

1Mbps 10Mbps

.


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outline


GSM

UMTS

LTE


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GSM operation

the spectrum assigned to GSM is divided into sub-bands of

200 KHZ each.

the subbands cannot be used in adjacent cells

due to inter-cell interference

a frequency reuse map is necessary


1/3 of sub-bands used in each cell 1/7 of sub-bands used in each cell

a transmitter (a dedicated amplifier) is necessary for each sub-

band in the cell.


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Time Division Multiple Access operation

several frequency sub-bands of 200 KHZ each

each sub-band is allocated for different users at different times

the time frame of 4.62 ms is divided into 8 time slots

but the transmitter serves up to 7 users (one TS for signalling)


Transmitters

Time slots


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example capacity of a GSM cell

exercise



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outline


GSM

UMTS

physical layer

capacity calculations LTE


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Code Division Multiple Access

everybody transmits at the same

time-frequency resources.

each transmitter has its own code

the receiver decodes the signal and

views the others' signals as residual

interference.



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spreading process



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downlink spreading codes

Walsh code:

W(0,1) = 1

W(0,2) = 1, 1

W(1,2) = 1,-1

W(0,4) = 1, 1, 1, 1

W(1,4) = 1,-1, 1,-1

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

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

W(0,8) = 1, 1, 1, 1, 1, 1, 1, 1

W(1,8) = 1,-1, 1,-1, 1,-1, 1,-1

W(2,8) = 1, 1,-1,-1, 1, 1,-1,-1

W(3,8) = 1,-1,-1, 1, 1,-1,-1, 1


W(4,8) = 1, 1, 1, 1,-1,-1,-1,-1

W(5,8) = 1,-1, 1,-1,-1, 1,-1, 1W(6,8) = 1, 1,-1,-1,-1,-1, 1, 1

W(7,8) = 1,-1,-1, 1,-1, 1, 1,-1

orthogonal codes, as synchronous transmissions

problem: multipath propagation that introduces delays


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UMTS capacity constraint

power of base station limited by Pmax

admission control constraint:

Com

n

i

iii PPMqNFPP ++=

max

1

0maxmax )(


intra-cell interference

intra-cell interference

noise


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capacity calculations

Exercise



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general capacity calculation

admission control constraint indicates that there is a resource

(power) shared by users of different demands

(position+service).

traffic c,i (Erlang) in zone i for class c.


-

= =

=C

c

n

i ic

Mic

nCMG

MMic

1 1 ,

,,1,1

!

1],...,Pr[

,


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outline


GSM

UMTS

LTE


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outline: LTE

physical layer

capacity calculations use case: mobile TV



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LTE context and E-UTRAN requirements

1 Tx antenna, 2 Rx antennas16 QAM modulation, code rate 5/6

56 Mbit/s

(71 Mbit/s for 64QAM)

Peak rate (Uplink)(in 20 MHz, FDD)

2 Tx and 2 Rx antennas- -

0.7 b/s/Hz/cell

Average cell spectrum

2 Tx and 2 Rx antennasMIMO transmission with linear

receiver

1.72 b/s/Hz/cell

(8.6 Mbit/s in 5 MHz)

Average cell spectrumefficiency (downlink)

2 Tx and 2 Rx antennas,64 QAM modulation, code rate 5/6

144 Mbit/sPeak rate (Downlink)(in 20 MHz, FDD)

Expected performance (based on analysis and simulations)

1 Tx antenna, 2 Rx antennas16 QAM modulation, code rate 5/6

56 Mbit/s

(71 Mbit/s for 64QAM)

Peak rate (Uplink)(in 20 MHz, FDD)

2 Tx and 2 Rx antennas- -

0.7 b/s/Hz/cell

Average cell spectrum

2 Tx and 2 Rx antennasMIMO transmission with linear

receiver

1.72 b/s/Hz/cell

(8.6 Mbit/s in 5 MHz)

Average cell spectrumefficiency (downlink)

2 Tx and 2 Rx antennas,64 QAM modulation, code rate 5/6

144 Mbit/sPeak rate (Downlink)(in 20 MHz, FDD)

Expected performance (based on analysis and simulations)


Assumptions:FDD, 30% retransmissions

~ 10 msUser plane latency(two way radio delay)

.

< 50 msecs (dormant->active)

< 100 msecs (idle ->active)

Connection setuplatency

Assumptions:FDD, 30% retransmissions

~ 10 msUser plane latency(two way radio delay)

.

< 50 msecs (dormant->active)

< 100 msecs (idle ->active)

Connection setuplatency


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the 3M of LTE

Multi-carrier Frequency dimension

Allow for spectrum flexibility and higher bandwidths.

Data rate = Bandwidth [Hz] x Spectrum efficiency [bps/Hz]

Multi-antenna (MIMO) Spatial dimension


Information Theory:Max. spectrum efficiency increases linearly with the number ofantennas.

Multi-Layer Cross-layer optimization (PHY, MAC, RLC)

Packet oriented radio interface Low latencies and higher spectrum efficiencies.

l i i h f di i


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multi-carrier the frequency dimension

Orthogonal Frequency Division Multiplexing (OFDM)

Facilitates equalization at the receiver

Divides bandwidth in narrowband sub-carriers


Time-frequency resources can be allocatedto data and control channels

TimeFrequency

Spectrumallocation1.25 - 20 MHz

1ms sub-frame (LTE DL)

L1/L2Control User A User B

TimeFrequency

Spectrumallocation1.25 - 20 MHz

1ms sub-frame (LTE DL)

L1/L2Control User A User B

M lti t th ti l di i (1/2)


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Multi-antenna the spatial dimension (1/2)

MIMO increases spectrum efficiency

NTX NRX


Theoretical Maximum: Spectrum Eff. = min(NTX, NRX) x Single antenna Eff.

Yes but

Additional antenna branches are costly especially on the terminal side

Achievable rates highly depend on propagation conditions

Mobile feedback required for high rates -> limitation of supported speeds

Different and adaptive solutions required depending on thedeployment scenario (coverage vs. rate trade-off).

M lti t th ti l di i (2/2)


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Multi-antenna the spatial dimension (2/2)

multi-antenna mechanisms in E-UTRAN downlink

Space diversitySpace diversitySpace diversitySpace diversity for improved robustness

of common control channels and

for users with high speed and/or low rate

BeamformingBeamformingBeamformingBeamforming for coverage

limited deployments

Spatial multiplexingSpatial multiplexingSpatial multiplexingSpatial multiplexing for high rates near

A) Transmit diversity-> Increased robustness

B) Beamforming-> Increased coverage


Adaptive selection of number of layers.

Spatial multiplexing of usersSpatial multiplexing of usersSpatial multiplexing of usersSpatial multiplexing of users in scenarios

with high user density and low rate traffic

C) Spatial multiplexing-> Increased throughput

D) Multi-user beamforming (SDMA)-> Increased capacity

M lti la er Fast packet sched ling


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Multi-layer Fast packet scheduling

Cross-layer design (Layer 1 Layer 2)

Time

Fast fading

~~~~Achievable

Throughput

User 1User 1User 1User 1


Fixed ressource

allocation

userthroughputTransmission time

Time

Fast fading

~~~~Achievable

Throughput



Fixed ressource

allocation

Fixed ressource

allocation

userthroughputTransmission time

Circuit oriented andlayered design


Usage of terminal feedback for resource allocation and phy-layer configuration

Cross-layer mechanisms already implemented in HSDPA.

Extension to frequency adaptive scheduling and adaptive MIMO transmission

Time

Fast fading

~~~~AchievableThroughput



Intelligentschedulingwith feedback

globalthroughput

Multi-userdiversity gain

bad

good

Time

Fast fading

~~~~AchievableThroughput



Intelligentschedulingwith feedback

globalthroughput

Multi-userdiversity gain

bad

good

Packet oriented andcross layer design

no intra cell interference but inter cell interference


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no intra-cell interference, but inter-cell interference

remains an issue

no intra-cell


n er erence as

chunks areorthogonal

inter-cell interference

is due to collisions

between chunks

used in different cells

link budget for throughput calculations


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link budget for throughput calculations




equipment parameters propagation model throughputreceived signals SINR



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link level curves

provide throughput vs SNR

curves according to:

multiple antenna use

(SISO, MIMO) channel model (AWGN,

Vehicular A, ..)


main output is the throughput versus distance


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main output is the throughput versus distance

stand-alone user throughput as a function of the distance to the base station

DL Cell Throughput versus Distance

18000

Max throughput


0

2000

4000

6000

8000

10000

12000

14000

16000

0,000 0,050 0,100 0,150 0,200 0,250

Distance (Km)

DL

CellThroughput(Kb

ps)

Throughput @ cell edge

interference calculations


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interference calculations

Exercise


outline: LTE


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outline: LTE

physical layer



how can link budget help capacity analysis?


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how can link budget help capacity analysis?

link budget gives the throughput vs distance:

throughput depends on position

cell can be decomposed into rings:

To simplify analysis

Homogeneous throughput in each ring



0

2000

4000

6000

8000

10000

12000

14000

16000

18000

0,000 0,050 0,100 0,150 0,200 0,250

Distance (Km)

DLCellThroughput(Kbps)

voice traffic: multi-Erlang analysis


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voice traffic: multi Erlang analysis

Consider voice traffic

Calls arrive with Poisson rate

Stay in communication for an average time T=3min

Require each 20 Kbps, or are blocked otherwise.

Example: 2 rings


,

One cell center (edge) user occupies 2% (4%) of the resources Admission control constraint: 2*Kcenter+4*Kedge


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g g p

Consider best effort traffic

Calls arrive with Poisson rate

Stay connected until transmitting a file of average size 1 Mbits

Example: 2 rings

1 Mbps for cell center, 500 Kbps for cell edge


in the cell until transmitting its file

the time necessary for the two users to transmit their files is 1+2=3

seconds

Within these three seconds, the volume of data transferred is equal

to 2 files= 2 Mbit.

The average throughput of the cell is then:

T=2 Mbit/3 second=667 Kbps

best effort traffic: Arithmetic versus harmonic mean


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The arithmetic mean of the throughput is:

Tarith=(1 Mbps+0.5 Mbps)/2=750 Kbps

This is different from the average throughput calculated

previously.

However, this corresponds to the harmonic mean:


harm= ps- + . ps - - = ps

This harmonic mean gives larger weights for cell edge users asthey stay longer in the cell

The harmonic mean is convenient to measure the cell

throughput

best effort traffic: Harmonic mean calculations


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2000

4000

6000

8000

10000

12000

14000

16000

18000

DLCellThroughput(Kbps)


Represents the maximal traffic that can be carried by the cell.

Used since the paper of Bonald el al., 2003.

0

0,000 0,050 0,100 0,150 0,200 0,250

Distance (Km)

best effort traffic: Processor sharing


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Objective:

Estimate QoS for a given traffic

Data users share the remaing resources

not used by streaming and voice ones (priority to

streaming/voice)

Fair in time but not fair in throu h ut


Processor sharing analysis can be used to assess capacity: Several classes corresponding to the number of rings

Gives average individual throughput at each position of the cell.

general model with a service mix


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predict the QoS based on marketing traffic forecasts.

determine the number of resources needed to ensure a target

QoS.

streaming traffic

multi-Erlanstreaming QoS


PS

data traffic

data QoS

categorydistribution

throughput pdf(link budget)

outline: LTE


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physical layer



Use case: TV traffic


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mobile TV traffic expected to explode

TV traffic evolution

5

6

7

8

unicast too greedy in resources:

spectrum resources

4

5

6

MHz


0

1

2

3

4

2009 2010 2011 2012 2013

E

rlang

0

1

2

3

2009 2010 2011 2012 2013

carriersof5

15

broadcast solution


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Point to Multipoint is the solution adapt to radio conditions

QPSK 1/2

16QAM 1/216QAM 3/4

64QAM 3/4


transmit with QPSK

advantage: simple

drawback: suboptimal

transmit with 16QAM

advantage: optimal

drawback: needs

feedback

total broadcast: Single Frequency Network


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if every body is watching TV

why not cooperating all base stations?


Interference is seen as a multipath propagation

drawback: tight synchronization between cells is needed

Delay and multipath impact


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Weight function for the constructive portion of a received SFN signal:

( ) 1 0

( )

( ) 0

CP

CP uCP CP u

u

CP u

w delay if delay T

T T delayw delay if T delay T T

T

w delay if T T delay

=

+ = < < +

= +

master ceri dimensionnement mobile

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