Cooperative Relaying Networks · 1 Cooperative Relaying Networks A. Wittneben Communication Technology Laboratory Wireless Communication Group Outline • Pervasive Wireless Access

1

Cooperative Relaying Networks

A. Wittneben

Communication Technology LaboratoryWireless Communication Group

Outline

• Pervasive Wireless Access• Fundamental Performance Limits• Cooperative Signaling Schemes• Joint Cooperative Diversity and Scheduling• The Rich Array/Poor Scattering Regime• The RACooN Laboratory

2

Pervasive Wireless Access Networks

Heterogeneous standards• IEEE 802.11 WLAN• IEEE 802.15 WPAN• IEEE 802.16 WMAN• (Hiperlan)• Bluetooth• DECT• various RFID• ..

• RFID tags, readers• sensors, actors• communication appliances• information access• information processing• backhaul access points• ...

Heterogeneous nodes

Available spectrum (approx.)• [email protected] (ISM)• [email protected] (ISM)• [email protected] (ISM)• [email protected] (ISM)• >3GHz@5GHz (UWB)•..

WLAN

Internetbackhaul

Sensornetwork

RFID

cellular:GSMUMTS

BluetoothWPAN

WMAN

Pervasive wirelessaccess

RFID

Body A

rea Netw

orks

Some Wireless Access Systems

100M

10M

1M

100k

10k

1k

1 3 10 30 100 range [m]

link throughput[bps]

11b

11a 11g

15.4

15.3

15.1

Sensor Networks

15.3a

WLAN

WPAN

Bluetooth

ZigBee

1000Mnext generation

WLAN • spatial multiplexing• f0 beyond 5 GHz

3

Hierarchical Heterogeneous Nodes

tags, sensors

sensors, actors

information access, peripherals

information processing

internet (backhaul) access

Network characteristics• hierarchical nodes• node density• „spot coverage“• uncoordinated, unlicensed „ad hoc“

infrastructureDesign objectives• data rate, QoS• range• position location• low cost• low EM exposure

Existing systems are insufficient

Outline


4

Capacity of Wireless Networks(Gupta/Kumar, Trans. On IT, 2000)

• n nodes optimally placed• Each node can transmit at W bits/sec• Traffic patterns, ranges, powers are

optimally assignes• Point-to-point coding• Gaussian interference model (no joint

decoding)• Main Result: Order of the aggregate

throughput capacity is

( )( ) = bit/secWn n n Wn

= Θ ⋅ Θ ⋅

λ

Capacity of Wireless Relay Networks(Gastpar/Vetterli, Infocom 2002)

• n Nodes randomly distributed over a disk• Source and destination randomly chosen• Ever node can hear every other node• Source transmits only half the time• Relay traffic pattern with one active

source-destination pair• Gaussian channels• Arbitrary complex network coding is used

• Main result:

logC n∞ =

source

destination

• average per-node power constraint• coherent combining on downlink

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Maximizing Degrees of Freedom in Wireless Networks(Borade et al., Allerton 2003)

Broadcast frommulti-antenna source(beamforming)

Multiple access tomulti-antenna destination(V-BLAST)

Two-hop network

multihop with MIMO intermediate nodes

Degrees of Freedom in Wireless Networks(Borade et al., Allerton 2003)

• Amplify-and-forward relays

• Establishes a distributed point-to-point MIMO channel

• Source uses same codebook as for a MIMO system (Gaussiancodebooks)

• For fixed k and n the systemachieves for high SNR a rate

Multi-hop network

(SNR) log(SNR)R n≈

2

PSNR =σ

6

Degrees of Freedom in Wireless Networks(Borade et al., Allerton 2003)

• No communication is possible when k ∞ (number of hops) and SNR is fixed

• Full degrees of freedom are achieved when k is fixed and SNR ∞

• Question: For which functions kn(SNR) full n degrees of freedom can beachieved?

• Answer:

SNR

(SNR)lim 0log(SNR)nk

→∞=

4.3 /ke SNR dB hop≤ ⇒

Outline


7

Cooperative Diversity

analog

diskret

MAC

LLC

Physical

Data Link

amplify, forward

decode, forwardfilter, amplify, forward

basestation

user 1

user 2

Distributed Antenna Uplink Scenario

centralprocessor

user 1 1R

2Ruser 2

1P

2P

*10k

*20k

0Z

+

0Y

basestation

0Z

+

0Y

Hk

X

kk

X

P

XX

2

1 2 2Z

P kR R R C

σ

⋅ = + <

1R

2R

• achievable rate region

• perfect CSI at transmitter• beamforming (coherent combining)

1 2P P P= +

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Multi-Access Uplink Scenario

user 1 1 1;W R

2 2;W Ruser 2

1P *10k

*20k

0Z

+

0Y

basestation

2

1 2 22 Z

P kR R R C

σ

⋅ = + < ⋅

1R

2R

• achievable rate region for

• coherent combining not possibledue to independent codebooks

• with CSI: power loading

1X

2X

X

2P

X

1 2 / 2P P P= =

2

101 22 Z

P kR C

σ

⋅ < ⋅

2

202 22 Z

P kR C

σ

⋅ < ⋅

User Cooperation Diversity

1W

2W

10P

*10k

*20k

0Z

+

0Y

basestation

1R

2R

• achievable rate region for

• perfect CSI• users share a part of their data• this part is transmitted coherently with

the same codebook

10X X

1 2 / 2P P P= =10

12

W

W

U

+1 10 10/UP k k⋅

X

20P

20X X

21

20

W

W

+

U

2 20 20/UP k k⋅

X

W∆

1 2W W W∆ = +

0W∆ =

[Sendonaris et al 98/02]

9

Outline


Multiuser diversity vs. low mobility

• In a large wireless network the probability is high that the base station can serve one high-data rate user -> multiuser diversity

• aggregate throughput (system throughput) can be maximized by always serving the user with the strongest channel

• disadvantage: in low mobility environments channel variations are not sufficiently large enough -> high delays at some user nodes

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Fairness and delay

• in asymmetric channels (near-far situation) adaptivescheduling is unfair => high delays even in high mobility environment

• challenge is to achieve multiuser diversity gains while providing certain amount of fairness

0 100 200 300 400 500 600 700 800-10

-5

0

5

10

15

20

25

30

35

time slots

SNR

[dB

]

SNR of asymmetric user channels

User 1User 2

Proportional Fairness

• Question: How to achieve fairness among users with different fading statistics?

• Solution: Serve user who has best SNR compared to its average SNR (within a given latency time-scale tc)

• Comments:– proportional fair scheduler normalizes the SNR of each user to a

similar average value– scheduler operates away from aggregate throughput optimum

11

Proportional Fairness and Low Mobility Environments

• in low mobility environments channel variations are not sufficient to achieve multiuser diversity gains with fairness

• introduce channel fluctuations artificially?

0 100 200 300 400 500 600 700 800-1

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

time slots

norm

aliz

ed S

NR

[dB

]

SNR of asymmetric user channels

User 1User 2

note different y-scale

Opportunistic Beamforming using dumb antennas(Viswanath, Tse, and Laroia, Trans. Inf. Theory 2002)

• basestation with multiple antennas• time-variant weights at each antenna• SNR feedback from all users• randomly swept beam and opportunistically send data to

best user

12

Slow Fading Environment: Before and after

• artificially introduced high mobility (time-variance)

Before After

Performance

• for large number of users performance of truebeamforming is achieved

• less feedback and channel measurements required

13

Distributed Relay networks

• amplify-and-forward relays introduce channel fluctuations by time-variant amplification gain at relays

Joint Cooperative Diversity and Scheduling(Wittneben/Hammerström Globecom 2004)

• 1% aggregate outage throughput is improved by a factor of nine if six active source/destination pairs are considered

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Outline


Array and Propagation Model

( ) ( )2 2 2a a ,0 0 a ,0 N a,0 0N N f / f N f with N 16 A / ≈ ⋅ ≡ ⋅ = ⋅ π ⋅ λ

( )( ) ( )2PL 0 TX RX PL,0 0x / 4 d G G x d / d

−γ= λ π ⋅ ⋅ ⋅ ⋅ ⋅

( )( )2 2 2PL 0 TX RX PL,0 Nx / 4 d G G x b / f= λ π ⋅ ⋅ ⋅ ⋅ ≡

/ 2λ

A

0dd

fixed distance

Number of antenna elements

Power path loss

in the sequel b=1 without loss of generality

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Some Capacity Considerations

Ergodic capacity: ( )SDSD H SD SDC E C H =

Instantaneous capacity: ( ) ( ) ( )( )( )aN2 k 2

SD SD 2 s a SD wk 1

C H log 1 P / N /=

= + ⋅ σ σ∑• no power loading• per complex dimension

SD SD,N N SD,N NH H b / f H / f= ⋅ ≡Channel matrix:• singular values ( ){ }k

SDσ

No scattering: ( )2SD 2 s a,0 wC log 1 P N /= + ⋅ σ( ) ( )1 1

SD,N a SD a NN N / fσ = ⇒ σ =[ ]SD,NH m,n 1=

( ) ( ) ( )( )N

2 2 2 2SD a N a,0 2 s N N w aC N f N E log 1 P / f / N

σ = ⋅ ⋅ + ⋅ σ σ

Rich scattering:[ ] ( )SD,NH m,n CN 0,1=

: one-dimensional pdf of singular values of SD,N aH 1/ N⋅( )Np σ

essentially independent of foraN aN 4≥

( ) ( ) ( )2 2SD a,0 s w s wC N / ln 2 P / A P /∞ = ⋅ σ ⋅ σ∼Asymptotic value :N af ; N → ∞

• power limited regime

1 2 3 4 5 6 7 80

5

10

15

20

25

30

35

40

45

50

55

normalized carrier frequency fN

capa

city

[bit/

chan

nel u

se]

Cf0_v1.m

rich scattering

no scattering

reality

rich scattering poor arraypoor scattering rich array

Rich array/poor scattering paradigm

would require > 256 relevant scatterers

?

16

Active Scatterer Concept(Wittneben/Rankov, IST 2003, SPAWC 2004)

Example: Wireless Distribution System for WLAN

• Network operates in infrastructuremode

• Channels are domiated by line-of-sight (WLAN at 24 GHz)

• Idle nodes as relays (activescatterers) to introduce artificalmultipath structure into effectivechannel

Active Scatterer Concept(Wittneben/Rankov, IST 2003, SPAWC 2004)

• One source/destination pair with Nantennas each

• K amplify-and-forward relays

• Channel shaping via activescattering for capacity gains

• Linear increase in capacity whenN<K spatial multiplexing gain

• Logarithmic increase in capacitywhen N>K array gain

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Distributed Antenna System (DAS) Scenarios(Wittneben/Rankov, URSI-EMTS 2004, VTC Fall 2004)

12.5m

source

destination

2a NN 4 f= ⋅

equispaced support nodes

2γ = no scattering

central processor

• decode DAS: decode&forward• linear DAS: linear processing; simple link adaptation

• random uniform placement• stationary• no antenna coupling

Access point:

Propagation model:

Source, destination:

DAS: 2-hop traffic pattern

Performance of LDAS and DDAS versus the carrier frequency fN

• total power constraint at sourceand support nodes

• no power loading across spatialsubchannels

• further details in [WittRank04]

DAS efficiently exploits rich array/poor scattering regime

1 1.5 2 2.5 3 3.5 45

10

15

20

25

30

35

40

45

50

55

10%

out

age

capa

city

normalized frequency fN

case6 Nr= 64 NaS= 64 NaD= 64 kRice= 1000000 r:T1 b:T2a g:T2b m:T2c k:T0

DDAS

LDAS

p2p

[WittRank04]: Distributed Antenna Systems and Linear Relaying for Gigabit MIMO Wireless, VTC Fall 2004

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Antenna spacing (16x16x16)-system

• fN = const

• robust performance

• residual spatial multiplexinggain for p2p

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 110

15

20

25

30

35

40

4510

% o

utag

e ca

paci

ty

normalized antenna spacing da/λ


DDAS

LDAS

p2p

compact antenna arrays feasible

Number of source/destination antenna elements (Nax16xNa)-system

• fN = const• LDAS: downlink eigenbeams

known• DDAS: no downlink CSI

• rich tradeoff

• residual spatial multiplexinggain for p2p

0 2 4 6 8 10 12 14 160

5

10

15

20

25

30

35

40

45

10%

out

age

capa

city

#source antennas Na


DDAS

LDAS

p2p

excellent performance of LDAS

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Outline


RACooN Laboratory at ETH Zurich

• 10 nodes• 5-6GHz• 80MHz bandwidth

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Initial Measurements

-5 0 5 10 15 20

x 10-8

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Direct

Relay magnitude of impulse response

Documents

Cooperative Relaying Networks · 1 Cooperative Relaying Networks A. Wittneben Communication Technology Laboratory Wireless Communication Group Outline • Pervasive Wireless Access