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Transcript
Cross layer design for
Wireless networks
Kavé Salamatian
LIP6-UPMC
Future Wireless Systems
Ubiquitous Communication Among People and Devices
Nth Generation Cellular
Wireless Internet Access
Wireless Video/Music
Wireless Ad Hoc Networks
Sensor Networks
Smart Homes/Appliances
Automated Vehicle Networks
All this and more…
Next generation network
architecture
Internetworking
Layer
Mobility
Services
Layer
Network
Service
Layer
Local
Service
Layer
Access
Management
Radio
Layer
Access
Layer
Access
Interface
Layer
Mobile
Terminal
Layer
Wireless
Interface
Layer
Mobile
Application
Layer
Internet
Wireless
PSTN
Radio Access Network
Mobile User Equipment
(e.g. Win9X, Palm OS)
Application
Network Server
(e.g. WinNT, Unix)
Radio Access Network
Radio
Resource
Mgmt
Application
IP Transport
(TCP, UDP, RTP)
Internet Protocol
(IP)
Ethernet Modem
Radio
Access
IP Transport
(TCP, UDP, RTP)
Transport
Agents
Transport
Agents
Radio Access
L2
L2
IP
Internet Protocol
(IP)
Access Core
L2
L2
Internet
Radio Access
L1
L1
Access Core
L1
L1
Radio-Optimized IP Networking
• Transparent to TCP/IP protocols
• Enables deployment of IP-based consumer applications
in next generation wireless systems
Ethernet ATM
Separation principles
 Application, transport and
physical layer can be
separated if :
No errors at physical layer
No losses and delays at
transport layer
No fluctuations in applications
rate
Each layer being perfect from
the point of view of other
layers
Application Signal
Transport
Packet
Physical
Bits
Challenges
 Wireless channels are a difficult and capacitylimited broadcast communications medium
 Traffic patterns, user locations, and network
conditions are constantly changing
 Applications are heterogeneous with hard
constraints that must be met by the network
 Energy and delay constraints change design
principles across all layers of the protocol stack
These challenges apply to all wireless networks,
but are amplified in ad hoc/sensor networks
Why is Wireless Hard?
The Wireless Channel
 Fundamentally Low Capacity: R< B log(1+SINR) bps
Spectrum scarce and expensive
 Received power diminishes with distance
 Self-interference due to multipath
 Channel changes as users move around
 Signal blocked by objects (cars, people, etc.)
 Broadcast medium – everyone interferes
d
…And The Wireless Network
Wireline Backbone
 Link characteristics are dynamic
 Network access is unpredictable and hard to
coordinate
 Routing often multihop over multiple wireless/wired
channels
 Network topology is dynamic
 Different applications have different requirements
Design objective
 Want to provide end-to-end Properties
 The challenge for this system is dynamics
Scheduling can help shape these dynamics
Adaptivity can compensate for or exploit these dynamics
Diversity provides robustness to unknown dynamics
 Scheduling, adaptivity, and diversity are most
powerful in the context of a crosslayer design
 Energy must be allocated across all protocol
layers
Multilayer Design
 Hardware
 Power or hard energy constraints
 Size constraints
 Link Design
 Time-varying low capacity channel
 Multiple Access
 Resource allocation (power, rate, BW)
 Interference management
 Networking.
 Routing, prioritization, and congestion control
 Application
 Real time media and QOS support
 Hard delay/quality constraints
Multilayer Design
Crosslayer Techniques
Adaptive techniques
Link, MAC, network, and application adaptation
Resource management and allocation (power control)
Synergies with diversity and scheduling
Diversity techniques
Link diversity (antennas, channels, etc.)
Access diversity
Route diversity
Application diversity
Content location/server diversity
Scheduling
Application scheduling/data prioritization
Resource reservation
Access scheduling
Key Questions
What is the right framework for crosslayer design?
What are the key crosslayer design synergies?
How to manage its complexity?
What information should be exchanged across layers,
and how should this information be used?
How do the different timescales affect adaptivity?
What are the diversity versus throughput
tradeoffs?
What criterion should be used for scheduling?
How to balance the needs of all
users/applications?
Single user example
WIFI : (171,133)
0
10
-1
10
-2
10
Packet Error Rate
-3
10
-4
10
-5
10
-6
10
1
2
3
4
5
6
SNR
7
8
9
10
Adaptive Modulation
and Coding in Flat Fading
Uncoded
Data Bits
Point
Selector
Buffer
log2 M(g) Bits
g(t)
One of the
M(g) Points
M(g)-QAM
Modulator
Power: S(g)
g(t)
To Channel
 Adapt transmission to channel
Parameters: power,rate,code,BER, etc.
Capacity-achieving strategy
 Recent Work
BSPK
4-QAM
16-QAM
Adaptive modulation for voice and data (to meet QOS)
Adaptive turbo coded modulation (<1 db from capacity)
Multiple degrees of freedom (only need exploit 1-2)
Adaptive power, rate, and compression with hard deadlines
Crosslayer design in multiuser
systems
• Users in the system interact (interference,
congestion)
• Resources in the network are shared
• Adaptation becomes a “chicken and egg” problem
• Protocols must be distributed
Wireless networks
They are formed by nodes with radios
There is no a priori notion of “links”
 Nodes simply radiate energy
Nodes Cooperation
 Decode and forward
 Why not: Amplify and
Forward
 Increase Signal for
Receiver
 Why not: Reduce
Interference at Receiver
How should node cooperates ?
 Some obvious choices
Should nodes relay packets?
Should they amplify and forward?
Or should they decode and forward?
Should they cancel interference for other nodes?
Or should they boost each other’s signals?
Should nodes simultaneously broadcast to a group of
nodes?
Should those nodes then cooperatively broadcast to
others?
What power should they use for any operation?
…
 Or should they use much more sophisticated
unthought of strategies?
Example: Six Node Network
Capacity Regions (Goldsmith)
Rij  0, ij  12,34, i  j
Multiple
hops
Spatial
reuse
SIC
(a): Single hop, no simultaneous
transmissions.
(b): Multihop, no simultaneous
transmissions.
(c): Multihop, simultaneous
transmissions.
(d): Adding power control
(e): Successive interference
cancellation, no power
control.
Optimal Routing
 The point R12  R34  1.64 Mbps
following scheduling :
is achieved by the
Adaptive Rate MAC (Kumar)
 Idea: Adapt transmission rate according to
channel quality
Change modulation to get higher rate if channel is good
Could send multiple packets at higher rates (A
suggested cscheme)
 Protocol details
RTS/CTS and Broadcast packets sent at lowest rate
Receiver measures strength of RTS
Communicates rate to sender in CTS
DATA and ACK at that rate
Interaction with Min Hop Routing Protocol
Most current routing protocols are min hop
Consider DSDV for example
Chooses long hops
But long hops => low signal strength => low rates
Switching off adaptation is better
Routing based approach
Luigi & al.
Routing in wireless network
 « Shortest path approche is not optimal »
 Physical channel is instable
 Each transmission inject interference in the
network
Interference reduce capacity
 Power management is needed
Make use of multi-rate and power control on WIFI card
L’architecture en couches n’est pas optimale
 Cross Layer approch
Maximise throughput
Gupta & Kumar
Rate
Transmission range
Node number
Throughput
To maximise throughput we have to maximise transmission
rate and reduce interference generated by each packets
Capacity Constraints
Cross-Layer Approach
Routing metric
Rate
Interference
Packet Error Rate
SIR
Interface characteristics
Next-Hop
Data-Rate
Transmission power
Interference
 Measurement: unrealistic
 More neighbor => More interference
 More power => More interference
 Defining a interference replacement function I(P)
 Minimise I(P) => Minimise Real interference
Packet Error Rate (I)
IP packet
IP packet
MAC
MAC
Convolution
Coder
Viterbi
Decoder
Interleaver
Deinterleaver
Modulator &
Scrambler
Interference
Noise
(White or fading)
Channel
Single Antenna
Multiple Antenna
Rake Receiver
Packet Error Rate (III)
 BER 

PERSIR   f 
 Pf E L 
Routing Strategy
• Rate (Mbps)
•Maximise
•Interference (mW)
• Minimise
•PER
• Minimise
•Power (mW)
• trade off for optimising
routing parameter
•NP-Complet Problème
Routingless approach
Ramin & al.
Ad-Hoc Network
 Ad Hoc Networks function by multi-hop transport
 Nodes relay packets until they reach their destinations
 Must of the traffic carried by the nodes is relay traffic
 The actual useful traffic per user pair is small
 Intermediate nodes relay the same information
 Duplicated information might be received by the receiver
More intelligent relaying is needed
Which packet to relay 
Which information to relay 
• The relay nodes must only send useful information
Coding for erasure channels
 MDS (Maximum Distance Separable) codes
Get k packets, generates n-k redundant packets
 Each combination of k packets out of n enable to retrieve
the initial packets
 Generating matrix C   I k k Bk ( n k ) 


• Each submatrix of
Bk( nk )
is invertible
Reed Solomon codes are MDS
 We suppose that sender generates m redundant
packets
 We suppose that relay generates l packets
How to choose m and l to achieve the bound
Achievability of the capacity bound for the
more capable case
 Choose a code length n. Knowing packet loss matix of the
netwok R and opt can be determined. We chose then
k
 nR, l  n  opt


 The code C  I k k Bk0( nk ) Bk1l is a MDS code
 The receiver is able to retrieve the k initial packets if it receives at
least k packets from sender and relay together
 This happen asymptotically with large n if the rate validate
the bound

W  X  I k k Bk0( n k )
 

X 1  W  Bk1l
1
p2
p1
W

X  W  I k k Bk0( n k )

p
W  X , X1  C
W
Comments & practical consideration
 Relay send only useful side information over the
channel
 The relay load is chosen as the minimal value
which maximize the global rate
 Each sender and relay can derivate the number of
needed redundant packets if it know the packet loss
probability matrix
 The proposed scheme can be implemented very
easily in WiFi based wireless network
Does not need any change to physical layer
Practical implementation
 15 node distributed randomly in the environment
One Sender-Receiver pair is chosen randomly
each node have two cart WiFi, with different frequency
channels f1 and f2
If one node receive the packets
 It can be a relay with probability p
The relay nodes broadcast information in the
environment
 There is not any routing protocol
 It is done in NS
Topology
600
500
Receiver
400
300
200
100
Sender
0
0
100
200
300
400
500
600
Throughput and relay load
6
10
5
10
4
10
3
10
2
10
-3
10
-2
10
-1
10
0
10
35
30
25
20
15
10
5
0
-3
10
-2
10
-1
10
0
10
Toward Software radio
Antenna
Common
DSP
platform
Tx
Chan
Interface
UpconD/A
verter
Channelizer
Interface
Wideband
transceiver
MCPA
Rx
Chan
A/D
Interface
Dup LNA RF/IF
Network ATM
I/F
Cellsite controller
middleware
• Common technology for multiple radio platforms
Conclusions
 Crosslayer design needed to meet requirements and constraints of
future wireless networks
 Key synergies in crosslayer design must be identified
 The design must be tailored to the application
 Crosslayer design should include adaptivity, scheduling and
diversity across protocol layers
 Energy can be a precious resource that must be shared by different
protocol layers
 Coming Challenges
 MIMO: how to take advantage of Multiple Antenna
 Software Radio: How to enable adaptation of physical layer
from upper layer
Interesting Question
MIMO or Ad Hoc, that’s the question?
Routing can be seen as a diversity
Not shortest path !