cooperative relaying networks · 1 cooperative relaying networks a. wittneben communication...
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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
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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
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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
• Pervasive Wireless Access• Fundamental Performance Limits• Cooperative Signaling Schemes• Joint Cooperative Diversity and Scheduling• The Rich Array/Poor Scattering Regime• The RACooN Laboratory
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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
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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
• Pervasive Wireless Access• Fundamental Performance Limits• Cooperative Signaling Schemes• Joint Cooperative Diversity and Scheduling• The Rich Array/Poor Scattering Regime• The RACooN Laboratory
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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]
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Outline
• Pervasive Wireless Access• Fundamental Performance Limits• Cooperative Signaling Schemes• Joint Cooperative Diversity and Scheduling• The Rich Array/Poor Scattering Regime• The RACooN Laboratory
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
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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
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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
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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
• Pervasive Wireless Access• Fundamental Performance Limits• Cooperative Signaling Schemes• Joint Cooperative Diversity and Scheduling• The Rich Array/Poor Scattering Regime• The RACooN Laboratory
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
?
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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
case2 Nr= 16 NaS= 16 NaD= 16 kRice= 1000000 r:T1 b:T2a g:T2b m:T2c k:T0
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
case3 Nr= 16 NaS= 16 NaD= 16 kRice= 1000000 r:T1 b:T2a g:T2b m:T2c k:T0
DDAS
LDAS
p2p
excellent performance of LDAS
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Outline
• Pervasive Wireless Access• Fundamental Performance Limits• Cooperative Signaling Schemes• Joint Cooperative Diversity and Scheduling• The Rich Array/Poor Scattering Regime• The RACooN Laboratory
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