Advanced telecommunication systems

Advanced telecommunication systems Part I : mobile network dimensioning Salah Eddine El Ayoubi

October 2010

outline

objective: ensuring QoS in mobile networks

dimensioning for ensuring coverage

dimensioning for ensuring capacity – GSM – UMTS – LTE – just before LTE: HSDPA – after LTE: LTE-A

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Salah Eddine EL AYOUBI – October 2010

outline




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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 coverage of any base station: – 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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QoS targets

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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What is spectrum ? Radio waves are characterized by their frequency, measured in Hertz (Hz)

f1

f2

300 MHz

30 MHz

VHF

f3

3 GHz

UHF

30 GHz

SHF

Spectrum is the continuous aggregation of these frequencies

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Main guidelines when managing spectrum

Spectrum shall be usable (not all frequencies are valuable for every type of radio access) coverage

Coverage frequencies

Spectrum shall be managed as efficiently as possible


Coverage too small

Terminal too big

400

8

Capacity frequencies

1000

5000

Frequency (MHz)

How it works ?

f3

f3

f1

f2

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f1

f2

f3

f1

f2

High demand

Limited resource

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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

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propagation model


received signals

SINR

cell range


determine gains and losses due to equipments.

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

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

body loss LB: – due to the body of the user.

for an emitted power Pmax:

Pmax × G A useful power = LF LB

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propagation model



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propagation model


received signals

SINR

cell range

radio channel channel variations are due to – pathloss attenuation – shadowing (slow fading) – fast fading

Attenuation (dB)

Path Loss Shadowing Fast fading

Distance

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path loss is due to the distance between the transmitter and the receiver

shadowing is due to the obstacles between the transmitter and the receiver

fast fading is due to multipath propagation (reflections on obstacles that create multiple paths of the received signal)

for coverage dimensioning, focus is on the path loss, adding a margin for shadowing


use of propagation models

Ptx

Ptx pathloss

pathloss C

I

Serving BS

Interfering BS

propagation models allow to compute: – The received signal power (⇒ coverage maps) – The interfering power (⇒ QoS maps)

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a propagation model is the first building block of (almost) any radio planning tool


path loss models

free space propagation  4πD   4πDf  Pathloss =   =  λ c     2

2

D

– only valid for line of sight, without multimulti-path – these conditions are not met in cellular networks

statistical models (e.g. Okumura-Hata)

Pathloss[dB ] = A + B ⋅ log(D ) with 20 ≤ B ≤ 40

– simple models with A & B statistically tuned for typical environments (urban, etc.) – no geographical data required – useful for dimensioning 17


e.g. urban environment

D

received signals



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propagation model


received signals

SINR

cell range

received signals

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

Pmax × G A 10 10 received power = × LF LB PL(d ) – PL(d)=path loss at distance d – ξ shadowing variable

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SINR



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propagation model


received signals

SINR

cell range

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 the position 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):

received power SINR = received interference + noise

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

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cell range



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propagation model


received signals

SINR

cell range

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

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in general, the limiting link for coverage is the uplink as mobiles have low emitted powers.


example coverage of a cell

exercise

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outline




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Erlang-like capacity

need to install resources: – until a target Quality of Service (QoS) is achieved for users – example: number of frequency carriers per cell

user perceived QoS includes: – blocking rates for real-time calls – download time for FTP-like users

this is called Erlang-like capacity: – reference to mathematician Agner Krarup Erlang

– example Erlang-B law.

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Erlang-B law Erlang table

probability of call loss:

– – – –

B=blocking rate E=traffic intensity C= number of circuits Each call uses one circuit

N

0.0001 0.001

100 95 90 85 80 75 70 65 60 55 50 45 40 35 30 25 20 15 10 5

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85

A simple Erlang calculator can be found at:

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

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0.01

the race for bit rates in mobile networks Mobility

2000

1995

WIDE AREA MOBILITY

2010

2005

HSDPA HSDPA GSM

EDGE EDGE

GPRS

UMTS UMTS HSUPA

HSPA HSPA

LTE

++

4G? 4G?

Mobile DVB-xTV 802.16m

SHORT RANGE

B3G

MOBILITY

Fixed FixWimax FIXED

WLAN WLAN

Data Rate 10kbps

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100kbps


1Mbps

10Mbps

100Mbps

outline




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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

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1/7 of sub-bands used in each cell a transmitter (a dedicated amplifier) is necessary for each subband in the cell.


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

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Time slots

example capacity of a GSM cell

exercise

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outline




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outline: UMTS

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physical layer

admission control

capacity calculations


Code Division Multiple Access

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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.


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, 1 W(6,8) = 1, 1,-1,-1,-1,-1, 1, 1 W(7,8) = 1,-1,-1, 1,-1, 1, 1,-1

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orthogonal codes, as synchronous transmissions

problem: multipath propagation that introduces delays


uplink spreading codes (1/2)

ak

Maximum Length (ML) sequence

sequence determined by the XOR feedbacks.

if register of length R, sequence of period L=2R-1

XOR of a sequence with a shifted version of it gives another version of the same ML sequence.

characterized by irreductible polynom: f ( x) =

c ( n) =

1≤ k ≤ R

∑ a c(n − k ),

c(n + j ) =

k

mod 2

c ( n) ⊕ c ( n + j ) =

∑ a c(n − k + j ) k

mod 2

∑ a c(n − k ) ⊕ c( n − k + j ) k

mod 2

d ( n ) = c ( n) ⊕ c ( n + j ) =

1≤ k ≤ R

∑ a d (n − k ) k

mod 2 40


∑a x k

mod 2

1≤ k ≤ R

1≤ k ≤ R

0≤ k ≤ R

k

uplink spreading codes (2/2)

inter-correlation between ML sequences may be large.

for obtaining good correlation properties, Gold codes are generated by EXOR-ing some preferred pairs of ML-sequences

Gold demonstrates that, if we choose carefully two ML sequences of length L=2R-1, characterized by polynoms f(x) and g(x), such that inter-correlation is low, the ML sequences of length L generated by z(x)=f(x).g(x) have also low correlation.

not orthogonal but with low correlation for cases where transmitters are not synchronized

R=6

f(x)=x6+x+1, g(x)=x6+x5+x2+x+1

z(x)=x12+x11+x8+2x7+3x6+x5+x3+2x2+2x+1 =x12+x11+x8+x6+x5+x3+1

sequence of 22R-1, divided into 2R+1 sequences of length L. 41


dealing with inter-cell interference

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scrambling codes (Gold code) separate also cells in the downlink.

inter-cell interference is reduced as if it were a transmission from the same cell.


outline: UMTS

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physical layer

admission control



downlink SINR model 1.

r0

Pmax to share

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the SINR for a mobile depends on the distance r0 from the BS, as inter-cell interference increases at cell edge.

cell decomposition

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1.

the SINR for a mobile depends on the distance r0 from the BS, as inter-cell interference increases at cell edge.

2.

to simplify the problem, divide the cell into concentric rings

3.

a mobile is thus charcterized by its service and its position in the cell.

4.

calculate powers and SINRs.

5.

apply admission control: emitted power< maximal power.

emitted power

zone i is characterized by: – path loss qi,l with cell l – interference factor Fi =

qi ,0

∑q l ≠0

i ,l

service c characterized by target quality: β c = – S: spreading factor

SINR c S + α .SINR c

multi-path propagation introduces a orthogonality factor α

a power PCom is used for signalling

adjacent cells have average load χ

number of users of class c in zone i is Mi,c

the total transmitted power is

PCom +

Ptot =

n

C

∑ (χ P

max Fi

i =1

1−α


∑β M c

c =1

n

C

∑ (∑ β M c

i =1

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+ N 0 qi )(

c =1

i ,c )

i ,c )

admission control

power of base station limited by Pmax

admission control constraint: n

∑ (αP

max

+ χ Pmax Fi + N 0 qi )(

i =1

C

∑β M c

c =1

intra-cell interference noise intra-cell interference

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i ,c )

≤ Pmax − PCom

outline: UMTS

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physical layer

admission control




admission control constraint indicates that there is a resource (power) shared by users of different demands (position+service).

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

multi-Erlang analysis is suitable:

1 Pr[ M 1,1 ,..., M C ,n ] = G

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C

n

∏∏ c =1 i =1

ρ c,i M c ,i M c ,i !


Exercise

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outline




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outline: LTE

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physical layer

throughput calculations


use case: mobile TV


Beyond 3G context and E-UTRAN requirements Expected performance (based on analysis and simulations) Peak rate (Downlink) (in 20 MHz, FDD)

144 Mbit/s

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

56 Mbit/s (71 Mbit/s for 64QAM)

1 Tx antenna, 2 Rx antennas 16 QAM modulation, code rate 5/6

Average cell spectrum efficiency (downlink)

1.72 b/s/Hz/cell (8.6 Mbit/s in 5 MHz)

2 Tx and 2 Rx antennas MIMO transmission with linear receiver

Average cell spectrum efficiency (uplink)

0.7 b/s/Hz/cell (3.5 Mbit/s in 5 MHz)

2 Tx and 2 Rx antennas No Multi-user - MIMO

User plane latency (two way radio delay)

~ 10 ms

Assumptions: FDD, 30% retransmissions

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

Connection setup latency

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< 50 msecs (dormant->active) < 100 msecs (idle ->active)


the 3M of Beyond 3G similar principles are used by most beyond 3G air interfaces - the physics are the same for everybody !

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Multi-carrier

Multi-antenna (MIMO)

Multi-Layer

– Frequency dimension – Allow for spectrum flexibility and higher bandwidths. – Data rate = Bandwidth [Hz] x Spectrum efficiency [bps/Hz]

– Spatial dimension – Higher spectrum efficiencies – Information Theory: Max. spectrum efficiency increases linearly with the number of antennas.

– Cross-layer optimization (PHY, MAC, RLC…) – Packet oriented radio interface – Low latencies and higher spectrum efficiencies.


fast fading parameters (1/3)

fundamental parameters of the fast fading channel Remote Scatterer Local-to-mobile Scatterers

- delay spread (frequency selectivity) - maximum delay: tmax - coherence band: Bc = 1/tmax

Terminal v Basestation

- Bc=maximum bandwidth over which two frequencies of a signal are likely to experience correlated fast fading.

Remote Scatterer

- if the symbol duration is much larger than tmax, impact of delay spread is negligible.

tmax 55



fundamental parameters of the fast fading channel -Doppler spread (time selectivity)

Remote Scatterer Local-to-mobile Scatterers

- Mobile speed v - serving frequency fC

Terminal v Basestation Remote Scatterer

- Maximum doppler: fD = fC x v/c0 - Coherence time: Tc = 1 / (2 fD)

- signal arrives at the receiver within the interval [fC-fD,fC+fD] - if the baseband signal bandwidth is much greater than fD the effects of Doppler spread are negligible.

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fundamental parameters of the fast fading channel - angle spread (spatial selectivity)

Remote Scatterer Local-to-mobile Scatterers

Terminal v Base station Remote Scatterer

- difference in angles of arrival/departure - coherence distance is the maximum spatial separation over which the channel response can be assumed constant.

-for small angle spread, coherence distance is large -for large angle spread, coherence distance is small (e.g. in mobile communications).

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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 – Simple frequency domain equalization

– Time-frequency resources can be allocated to data and control channels – Various spectrum allocations can be addressed with the same technology

– E-UTRAN uses Single –Carrier FDMA (SC-FDMA)

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L1/L2 Control

User A

User B

Spectrum allocation 1.25 - 20 MHz

– Modified scheme may be needed in uplink – Similar properties than OFDM, but allows for cheap power amplifiers at the terminal.

Frequency

– OFDM Access (OFDMA) provides flexibility for resource allocation

Time

1ms sub-frame (LTE DL)

h*0

User K Modulation Coding

+ TG

- TG

FFT

Symbol mapping

. . .

Coding

S/P

0

P/S

User 1 Modulation

IFFT

multi-carrier … the frequency dimension OFDM parameters and signal design

h*Nc-1

Symbol demapping

NC -1

Nc narrowband sub-carriers

design rules – Avoid inter symbol interference: Guard interval (TG) > Maximum Channel delay (tmax) – Avoid inter carrier interference: Carrier spacing (∆f=1/TS) >> max. Doppler spread (2fD) – Limit overhead and ensure time invariance: TG ~0.25TS, TS+TG << Tc – Number of carriers is around 60-80% of FFT size to ensure spectrum emission mask.

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Multi-carrier … the frequency dimension Basic parameters of E – UTRAN Downlink

Frequency

L1/L2 Control

User A

User B

Time

20 MHz

1ms sub-frame (LTE DL)

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Multi-carrier … the frequency dimension

SC - FDMA signal design g*0

0 + TG

0 NC -1

SC - FDMA properties – Lower Peak to Average Power Ratio – Flexible resource size in frequency – Contiguous resource allocation required – Some residual interference between users 61


- TG

FFT

g*N

S/P

P/S

User 1

IFFT

Coding

DFT

. . .

User 1 Modulation

IDFT

h*0

User 2 h*N

IDFT

Multi-carrier … the frequency dimension E-UTRAN uplink sub-frame format – Same basic parameters as downlink – Contiguous resource allocation – Frequency hopping between slots Spectrum allocation (half sub-frame) and between sub-frames allowed for diversity. 1.25 - 20 MHz – Control only channels are Modulated allocated on both sides part of band of the band. ~ 60% – If data allocation exists control is multiplexed with data in the same resource.

Frequency

L1/L2 Control

1ms Normal Sub-frame

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User A

User B

Multi-carrier … the frequency dimension

frequency adaptive scheduling – Choose best time frequency resources based on channel quality feedback – Additional scheduling dimension compared to HSDPA (time only) – Reliable feedback can only be obtained for low speed users

interference coordination – Power restrictions allow for soft/adaptive frequency re-use

P(f)

2

Cell 1 f

– Gains seen in particular for varying load distributions

7

3

P(f)

Cells 2, 4, 6

1

f

6

4

P(f)

Cells 3, 5, 7 5 f

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Multi-antenna … the spatial dimension

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

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Different and adaptive solutions required depending on the deployment scenario (coverage vs. rate trade-off). Salah Eddine EL AYOUBI – October 2010


multi-antenna mechanisms in E-UTRAN downlink – Space diversity for improved robustness of common control channels and for users with high speed and/or low rate – Beamforming for coverage limited deployments

A) Transmit diversity -> Increased robustness

B) Beamforming -> Increased coverage

C) Spatial multiplexing -> Increased throughput

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

– Spatial multiplexing for high rates near the base station Adaptive selection of number of layers. – Spatial multiplexing of users in scenarios with high user density and low rate traffic

Only single antenna transmission considered in E-UTRAN uplink – Spatial multiplexing of users with multiple antennas at the base station receiver.

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Transmit diversity – Space diversity takes advantage of spatial A) Transmit diversity de-correlation to mitigate fast fading -> Increased robustness – Large antenna spacing or cross-polarized setups are preferred. – Receive diversity does not require a specific scheme and always gives gain, even for high fading correlation (>3dB for 2 Ant). – Transmit diversity schemes rely on redundancy transmitted from the different antennas and can work with single receive antenna. – Low correlation between antennas is essential since no power gain is achievable at the transmitter (power is distributed over antennas). – Space-Time Block Codes (or Space-Frequency Block Codes with OFDM) are low complex transmit diversity schemes.

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Transmit diversity in E-UTRAN – Transmit diversity can be applied to all downlink A) Transmit diversity channels in E-UTRAN (broadcast, control, data) -> Increased robustness – Basic scheme is Space Frequency Block Coding (SFBC) Orthogonal encoding avoids interference between symbols and simplifies the receiver (linear receiver is sufficient)

– Transmit diversity can be combined with multi-layer transmission using so-called cyclic delay diversity (CDD). 67



Beamforming – Beamforming concentrates energy to increase transmission rates at cell edge. B) Beamforming -> Increased coverage – Small antenna spacing and spatially correlated fading (small angle spreads) are preferred. – Channel state information (CSI) needed at transmitter (at least Direction(s) Of Arrival, DOA) – CSI can be obtained from uplink estimations (in particular in TDD systems) or from terminal feedback (costly). – Beamformed dedicated (user specific pilots) are needed to enable channel estimation at the terminal. – Broadcast and control channels cannot be beamformed. – DL Coverage is determined by these channels – Common reference signals are needed for broadcast & control.

– Calibration of antenna arrays is a practical technical challenge. 68



Beamforming illustrated:

Single-user approach – maximisation of the SNR. – implicit interference reduction – knowledge of user DoA

Multi-user approach – Maximisation of the SINR. – Explicit interference reduction – Knowledge of all DoAs

Antenna: ULA, M = 8 Users: 2 (Car: 1 DOA/ Phone: 2 DOAs) 69



Beamforming in E-UTRAN – Dedicated reference signals for a B) Beamforming single stream are supported. -> Increased coverage – Terminal estimates CQI from common reference signals, BS estimates beamforming gain for link adaptation. – BF gain is approximately 10log(M) dB – Codebook based pre-coding (~fixed beams) is supported and can also be combined with multi-layer transmission. – Mobile feeds back index of preferred pre-coding vector and can obtain channel estimates from common pilots multiplied by known pre-coding vector.

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Spatial multiplexing C) Spatial multiplexing

– Exploits good channel conditions to -> Increased throughput transmit via parallel layers. – Prefers rich scattering and un-correlated fading (large antenna spacing's or cross-polarized setups) – Transmitter scheme: FEC

N spatial layers

FEC

Mod. Mod.

CQI feedback for link adaptation

Precoding wN

M Txantennas

Precoding w1

Feedback of pre-coding vector index

– Receiver needs as many antennas as layers to be received. 71



Spatial multiplexing receiver


– Serial Interference Cancellation (SIC) receiver: Detect first codeword, if CRC correct re-generate interference contribution and subtract before decoding second codeword, …

Space Time LMMSE

Symbol detection

Source: A. Saadani

Serial Interference Cancellation 72



Spatial mutliplexing in E-UTRAN – Up to 2 codewords per user. – Coverage vs. Rate trade-off:


Source: Ericsson 73



Multi-user MIMO – Different layers can be transmitted D) Multi-user beamforming (SDMA) to different users in downlink. -> Increased capacity – E-UTRAN uses same codebook as for single user multiplexing. – Challenge to estimate CQI at terminal, since potential interference of other users is not known in advance. – Multi-user MIMO can enhance capacity in the uplink. – Transparent to the UE, only separable reference signals need to be used. – Multi-user MIMO is only useful for medium/low rate services with very high user densities. – Control signaling will become the limiting factor for user capacity. 74


Multi-layer – packet oriented radio

Fast packet scheduling in E-UTRAN – Reduced transmission interval of 1ms – Fast packet scheduling – Fast link adaptation and cross-layer design

Benefits – Reduced latency – Performance gains from adaptive configuration and multi-user diversity

Yes but… – Amount of signaling is increased -> higher overheads – Robustness to feedback errors and high velocities

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Multi-layer – packet oriented radio

Cross-layer design (Layer 1 – Layer 2) Fast fading

Transmission time

user throughput

~ Fixed ressource allocation

Achievable Throughput

global throughput

~ Achievable Throughput

Time

User 1

good

Multi-user diversity gain bad

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Circuit oriented and layered design

User 2

Time

Fast fading

User 1

Intelligent scheduling with feedback

Packet oriented and cross layer design

User 2

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 Salah Eddine EL AYOUBI – October 2010

Uplink power control in E-UTRAN Data

Interference coordination interference

Intra-cell power control To control Received Data Quality

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Inter-cell power control To control Received Interference

Combination of open loop power control with closed loop adjustments

Closed loop updates are send les frequently than for UMTS (<200 Hz) No intra-cell interference between users

Regular updates are send for power control of control channels

A periodic updates are send together with the UL scheduling grant

Inter-cell interference coordination is achieved via NodeB-NodeB communication. Salah Eddine EL AYOUBI – October 2010

Uplink power control in E-UTRAN

Basic formula implemented in the terminal: P = min ( Pmax , 10 log M + Po + α x PL + delta_mcs + f(delta_i))

78

Po : UE specific offset

α : Fractional Path-Loss compensation (cell specific)

M : the number of assigned RBs in the uplink grand (only for data)

delta_mcs : MCS specific correction

delta_i : cumulative or absolute correction value per UE signalled in the UL grant (data channels) or periodically (control channels)

Discussion still ongoing in particular on the interactions with interecell coordination


outline: LTE

79

physical layer



use case: mobile TV


what is interference in OFDMA?

80

no intra-cell interference

inter-cell interference is due to collisions between chunks


interference calculations

Exercise

81


link budget for throughput calculations



82

propagation model


received signals

SINR

throughput

link level curves

provide throughput vs SNR curves according to: – multiple antenna use (SISO, MIMO) – channel model (AWGN, Vehicular A, ..) – speed

83


main output

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

Max throughput DL Cell Throughput versus Distance 18000 DL Cell Throughput (Kbps)

16000 14000 12000 10000 8000 6000 4000 2000 0 0,000

84


0,050

0,100 0,150 Distance (Km)

0,200

0,250

Throughput @ cell edge

application: impact of some design parameters inter-site distance impact on DL average cell throughput: – when the cell is larger, a larger proportion of users is at cell edge

neighboring cell load impact on DL average cell throughput:

DL average cell throughput vs ISD 6.0 DL average cell throughput (Mbps)

5.5 5.0 4.5 4.0 3.5 0

2

3 4 Inter-site distance (km)

5

6

DL average cell throughput vs DL load 16.0 DL average cell throughput (Mbps)

– when the load of neighboring cells increases, inter-cell interference increases

1

14.0 12.0 10.0 8.0 6.0 4.0 0%

85


20%

40% DL load (%)

60%

80%

outline: LTE

86

physical layer



use case: mobile TV


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 DL Cell Throughput versus Distance 18000 DL Cell Throughput (Kbps)

16000 14000 12000 10000 8000 6000 4000 2000 0 0,000

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0,050



0,200

0,250

voice traffic: multi-Erlang analysis

Consider voice traffic – Calls arrive with Poisson rate λ – Stay in communication for an average time T=3min – Require each 20 Kbps, or are blocked otherwise.

Example: 2 rings – 1 Mbps for cell center, 500 Kbps for cell edge – One cell center (edge) user occupies 2% (4%) of the resources – Admission control constraint: 2*Kcenter+4*Kedge<100

Multi-Erlang analysis can be used to assess capacity: – Several classes corresponding to the number of rings – Gives blocking rates

88


Best effort traffic: average cell throughput

Consider best effort traffic – Calls arrive with Poisson rate λ – Stay connected until transmitting a file of average size 1 Mbits

Example: 2 rings – 1 Mbps for cell center, 500 Kbps for cell edge – One cell center (edge) user stays in average 1 second (2 seconds) 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

89


Best effort traffic: Arithmetic versus harmonic mean

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: Tharm={[(1 Mbps)-1+(0.5 Mbps)-1]/2}-1=667 Kbps

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

The harmonic mean is convenient to measure the cell throughput


Best effort traffic: Harmonic mean calculations DL Cell Throughput versus Distance 18000 DL Cell Throughput (Kbps)

16000 14000 12000 10000 8000 6000 4000 2000 0 0,000

91

0,050


0,200

0,250

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

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


Best effort traffic: Processor sharing

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 throughput

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.

92


general model

predict the QoS based on marketing traffic forecasts.

determine the number of resources needed to ensure a target QoS.

streaming traffic

streaming QoS multi-Erlang

data traffic category distribution

PS data QoS

throughput pdf (link budget) 93


outline: LTE

94

physical layer



use case: mobile TV


Use case: TV traffic

mobile TV traffic expected to explode

unicast too greedy in resources: spectrum resources

TV traffic evolution 6

8 7

Erlang

6 5

×15

4 3 2 1 0 2009

95

carriers of 5 MHz

5

4

3

2

1

2010

2011

2012


2013

0 2009

2010

2011

2012

2013

broadcast solution

Point to Multipoint is the solution

adapt to radio conditions QPSK 1/2 16QAM 1/2 16QAM 3/4 64QAM 3/4

96

transmit with QPSK ½

transmit with 16QAM ½

advantage: simple

advantage: optimal

drawback: suboptimal

drawback: needs feedback


total broadcast: Single Frequency Network

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

97


Delay and multipath impact

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

w(delay ) = 1 if 0 ≤ delay ≤ TCP w(delay ) =

TCP + Tu − delay Tu

if TCP < delay < TCP + Tu

w(delay ) = 0 if TCP + Tu < delay w(delay) 1

Tcp

98

Tu+Tcp

delay

Take into consideration of multipath propagation in the calculation


SINR calculation

Based on the weight function w() and the multipath table, the following equation for calculating average SINR per subcarrier for a MBSFN user M(r, θ) in cell 0 is derived: DL N 6

∑∑

SINRsubc ( M ) = where:

99

w( d ( M , j ) + dm ( p )) × rm ( p) × Psubc

j = 0 p =1

N

6

∑∑

DL (1 − w( d ( M , j ) + dm ( p )) ) × rm ( p ) × Psubc

j = 0 p =1

Shadowing is also to be considered. Salah Eddine EL AYOUBI – October 2010

PLDL M,j PLDL M,j

+ N th

SFN parameters LTE MBSFN FDD inputs

FDD Case 1

FDD Case 2

FDD Case 3

Carrier spacing (∆f)

15 kHz

15 kHz

7.5 kHz

Symbols number per subframe

14

12

6

Subcarriers number per RB (Resource Block)

12

12

24

MBSFN reference symbols number per RB

18

18

18

Cyclic prefix duration (TCP)

4.69 μs TCP = 144×Ts (for OFDM symbol #1 to #6) Ts = 1/ (2048 × ∆f)

16.67 μs TCP-e = 512×Ts (for OFDM symbol #0 to #5) Ts = 1/ (2048 × ∆f)

66.67 μs TCP-low = 1024×Ts (for OFDM symbol #0 to #2) Ts = 1/ (2048 × ∆f)

Extended Vehicular A (EVA)

100

relative delay (ns)

Relative Mean Power[dB]

0

0

1

30

-1.5

0.71

150

-1.4

0.72

310

-3.6

0.44

370

-0.6

0.87

710

-9.1

0.12

1090

-7.0

0.20

1730

-12.0

0.06

2510

-16.9

0.02


Power ratio [lin]

comparing TV deployment strategies

when TV traffic increases – unicasting it will be disastrous on other services… – single-cell broadcast (PtM) with modulation adaptation is a good intermediate solution – total broadcast (MBSFN) is the best solution…

101


outline




102


hybrid CDMA/TDMA access CDMA radio

reduced inter-cell interference residual intra-cell interference 103


no CDMA in the same cell – TDMA

how it works

104

scrambling code is used to reduce inter-cell interference

within the same cell, channelization code is used to separate signalling, UMTS and HSDPA signals.

HSDPA users share the same code in time

when there is at least one HSDPA user in the cell, the base station emits at maximal power


Radio model 1.

The SINR for a mobile depends on the distance r0 from the BS, as intercell interference increases at cell edge.

2.

To simplify the problem, divide the cell into concentric rings: A mobile is thus charcterized by its service and its position in the cell.

3.

Calculate R99 power and deduce the power remaining for HSDPA, as shown below. Pmax

HSDPA

Variable rate

data R99

Constant rate

voice R99 Common channels 105


admission control for R99

power of base station limited by Pmax

wa can show that admission control constraint remains the same as for pure R99 systems: n

∑ (αP

max

+ χ Pmax Fi + N 0 qi )(

i =1

C

∑β M c

c =1

intra-cell interference noise intra-cell interference

106


i ,c )

≤ Pmax − PCom

HSDPA throughput

4000

throughput (Kbps)

3500 3000 DCH=0 2500

DCH=20%

2000

DCH=40% DCH=60%

1500

DCH=65% 1000 500 0 0,040

0,060

0,080

0,100

0,120

0,140

distance to base station (Km)

107


0,160

0,180

UMTS/HSDPA model

UMTS traffic

multi-Erlang

UMTS QoS

PDCH

108

streaming traffic

multi-Erlang

streaming QoS

data traffic

PS

data QoS


outline




109


fast…

relays – increases useful signal

open issues: – choosing the relay type (AF, DF) – dimensioning of links

110


fast…

relays

coordinated multipoint (CoMP)

– increases useful signal

open issues: – choosing the relay type (AF, DF) – dimensioning of links

111


– increases useful signal – decreases interference

open issues: – choosing the CoMP type – dimensioning of backhaul

Advanced telecommunication systems

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