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Network engineering formobile networks
Salah Eddine El Ayoubi
Orange Labs
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
3 Salah Eddine Elayoubi Mobile Network Engineering
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
5 Salah Eddine Elayoubi Mobile Network Engineering
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
6 Salah Eddine Elayoubi Mobile Network Engineering
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
8 Salah Eddine Elayoubi Mobile Network Engineering
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
9 Salah Eddine Elayoubi Mobile Network Engineering
, . ., . ., . ., . .
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
10 Salah Eddine Elayoubi Mobile Network Engineering
Limited resource
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How to share spectrum
f3 f3
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f1 f1
f2
f2 f3 f1
f2
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objective: ensuring QoS in mobile networks
coverage in mobile networks
dimensioning radio interface for capacity
outline
12 Salah Eddine Elayoubi Mobile Network Engineering
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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.
14 Salah Eddine Elayoubi Mobile Network Engineering
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
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
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use of propagation models
Ptxpathloss
C
pathloss
Ptx
I
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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
17 Salah Eddine Elayoubi Mobile Network Engineering
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
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
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received signals
for a user situated at distance d from a base station:
)(dPLL
GP
powerreceivedF
Amax
=
19 Salah Eddine Elayoubi Mobile Network Engineering
PL(d)=path loss at distance d
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SINR
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
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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.
21 Salah Eddine Elayoubi Mobile Network Engineering
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.
22 Salah Eddine Elayoubi Mobile Network Engineering
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
+=
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a lower SINR means a larger Bit Error Rate (BER):
degraded QoS
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cell range
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
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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
25 Salah Eddine Elayoubi Mobile Network Engineering
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
objective: ensuring QoS in mobile networks
coverage in mobile networks
dimensioning radio interface for capacity
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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
-
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-
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
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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
30 Salah Eddine Elayoubi Mobile Network Engineering
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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objective: ensuring QoS in mobile networks
coverage in mobile networks
dimensioning radio interface for capacity
outline
31 Salah Eddine Elayoubi Mobile Network Engineering
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
32 Salah Eddine Elayoubi Mobile Network Engineering
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)
33 Salah Eddine Elayoubi Mobile Network Engineering
Transmitters
Time slots
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example capacity of a GSM cell
exercise
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objective: ensuring QoS in mobile networks
coverage in mobile networks
dimensioning radio interface for capacity
outline
35 Salah Eddine Elayoubi Mobile Network Engineering
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
38 Salah Eddine Elayoubi Mobile Network Engineering
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 )(
39 Salah Eddine Elayoubi Mobile Network Engineering
intra-cell interference
intra-cell interference
noise
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capacity calculations
Exercise
40 Salah Eddine Elayoubi Mobile Network Engineering
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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.
41 Salah Eddine Elayoubi Mobile Network Engineering
-
= =
=C
c
n
i ic
Mic
nCMG
MMic
1 1 ,
,,1,1
!
1],...,Pr[
,
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objective: ensuring QoS in mobile networks
coverage in mobile networks
dimensioning radio interface for capacity
outline
42 Salah Eddine Elayoubi Mobile Network Engineering
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)
44 Salah Eddine Elayoubi Mobile Network Engineering
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
45 Salah Eddine Elayoubi Mobile Network Engineering
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
46 Salah Eddine Elayoubi Mobile Network Engineering
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
47 Salah Eddine Elayoubi Mobile Network Engineering
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
48 Salah Eddine Elayoubi Mobile Network Engineering
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
User 2User 2User 2User 2
Fixed ressource
allocation
userthroughputTransmission time
Time
Fast fading
~~~~Achievable
Throughput
User 1User 1User 1User 1
User 2User 2User 2User 2
Fixed ressource
allocation
Fixed ressource
allocation
userthroughputTransmission time
Circuit oriented andlayered design
49 Salah Eddine Elayoubi Mobile Network Engineering
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
User 1User 1User 1User 1
User 2User 2User 2User 2
Intelligentschedulingwith feedback
globalthroughput
Multi-userdiversity gain
bad
good
Time
Fast fading
~~~~AchievableThroughput
User 1User 1User 1User 1
User 2User 2User 2User 2
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
50 Salah Eddine Elayoubi Mobile Network Engineering
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
link budget objective
maximum distance between a user and its serving base station while guaranteeing
a given quality of service
equipment parameters propagation model throughputreceived signals SINR
51 Salah Eddine EL AYOUBI June 2010
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link level curves
provide throughput vs SNR
curves according to:
multiple antenna use
(SISO, MIMO) channel model (AWGN,
Vehicular A, ..)
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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
53 Salah Eddine Elayoubi Mobile Network Engineering
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
54 Salah Eddine Elayoubi Mobile Network Engineering
outline: LTE
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outline: LTE
physical layer
capacity calculations use case: mobile TV
55 Salah Eddine Elayoubi Mobile Network Engineering
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
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DL Cell Throughput versus Distance
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
57 Salah Eddine Elayoubi Mobile Network Engineering
,
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
58 Salah Eddine Elayoubi Mobile Network Engineering
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:
59 Salah Eddine Elayoubi Mobile Network Engineering
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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DL Cell Throughput versus Distance
2000
4000
6000
8000
10000
12000
14000
16000
18000
DLCellThroughput(Kbps)
60 Salah Eddine Elayoubi Mobile Network Engineering
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
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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
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PS
data traffic
data QoS
categorydistribution
throughput pdf(link budget)
outline: LTE
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physical layer
capacity calculations use case: mobile TV
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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
64 Salah Eddine Elayoubi Mobile Network Engineering
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
65 Salah Eddine Elayoubi Mobile Network Engineering
transmit with QPSK
advantage: simple
drawback: suboptimal
transmit with 16QAM
advantage: optimal
drawback: needs
feedback
total broadcast: Single Frequency Network
7/30/2019 Master CERI Dimensionnement Mobile
66/70
if every body is watching TV
why not cooperating all base stations?
66 Salah Eddine Elayoubi Mobile Network Engineering
Interference is seen as a multipath propagation
drawback: tight synchronization between cells is needed
Delay and multipath impact
7/30/2019 Master CERI Dimensionnement Mobile
67/70
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
=
+ = < < +
= +