Cognitive Radio Multihop/- Mesh Networks

Cognitive Rad

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ultihop-/Mesh Networks

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Cognitive Radio Multihop-/Mesh Networks • GI/ITG KuVS Summer School Wireless Networking • Schloss Dagstuhl, September 10th, 2010 • slide 1

KUVS Summer School 2010

Cognitive Radio Multihop/-Mesh Networks

Andreas J. [email protected]

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Cognitive Multihop Radio Networks

Overview

� Wireless Mesh Networks

– Introduction

– Multi-Radio Mesh Networks

– Channel Assignment Schemes

� Cognitive Radio Multihop Networks

– Introduction

– Spectrum Sensing

– Spectrum Decision

– Spectrum Sharing

– Spectrum Mobility

� Conclusion

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Overview


– Introduction




– Introduction





� Conclusion

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Principles of W-LAN meshes

Current Wireless Networks

� Infrastructure-based– needs “wired” connectivity to access points.

– Deployment slow and expensive

Wired Backbone InternetR

X

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Multi-Hop Wireless Networks

InternetR

Every node is now Access Point AND Router

Every node is now Access Point AND Router

� Get rid of the wires!– mesh routing backbone created by grid of wireless APs

– Clients can associate with any access point.

– Small number of wireless hops to gateway

– Complete transparency: nodes forward voice, video and data traffic to and from nearby nodes wirelessly and ultimately to the internet

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Multi-Hop Wireless Networks

� Why interesting and study?

– No Wires!

– Properties:

• Robust & Fault tolerant

• Self-organising

• Self-configuring

• Self-healing

• No centralized management

A WMN is dynamically self-organized and self-configured, with

the nodes in the network automatically establishing and

maintaining mesh connectivity among themselves

A WMN is dynamically self-organized and self-configured, with

the nodes in the network automatically establishing and

maintaining mesh connectivity among themselves

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Introduction into Wireless Mesh Networks

Broadband Internet Access for rural/urban areas

� Metropolitan scale mesh networks � chaska.net– City of Chaska (8000 homes, 23.000 residents)

� 28% uptake after 2 years

– Nomadic broadband service for $17.99 per month

– Based on Tropos mesh products

• $600,000 infrastructure plus 2 month deployment

• 365 mesh routers � 95% coverage

• 60 backhaul links

Source: Tropos

Source: Tropos

Source: Tropos

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Introduction into Wireless Mesh Networks

WiFi Mesh for Developing Areas

� Extend Internet access into areas which do not have wired networking infrastructure.

� Reduced Infrastructure cost

� Typically semi-infrastructuredbackbone network (Mesh)

� Long distance links can be common

� Cheap, Off-the-shelf hardware

� Mission to support both social & economic development

� Useful for developing areas

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Challenges of W-LAN meshes

An Early Multi-Hop Wireless Network

What Challenges can we identify?What Challenges can we identify?

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Channel Access, Routing, QoS Management, etc.

� Wired networking protocols such as Ethernet perform poorly when used in wireless communication

Why? Because of media dependent differences

� You Should know:

– Hidden terminal problem

– Exposed terminal problem

– Collision detection problem

– Interference problem

– MAC layer/Routing in MANET

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MAC Layer

Medium Access Coordination

no parallel transmission

no parallel reception

Goal for MAC layer design:• avoid parallel interfering transmissions• do not hinder parallel non-interfering transmissions

Collision Domain Concept allows to infer achievable

capacity

Collision Domain Concept allows to infer achievable

capacity

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MAC Layer

Hidden Node Problem

hidden nodes

� Hidden Node Problem– A mesh node is hidden for an ongoing transmission if it is not able to sense the

ongoing transmission but its transmission would disturb the reception.– A node not in the sensing range of the transmitter but within the interference range

of the receiver

� HN-induced problems– Throughput degradation – Unfairness

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MAC Layer

Exposed Node Problem

� disabling of possible non-interfering parallel transmissions

� nodes that only receive RTS can transmit

� nodes that only receive CTS can receiveblocked nodes

RTS

CTS

Parallel transmissionsmight occur (except for ACK)

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� No collision detection in wireless communications

� In wireless you cannot listen while you send– Generally hardware is not flexible enough

– Only hear your own signal

• Your own signal at your antenna is much stronger than anyone else’s signal

� Consequently,– wireless can’t do collision detect like Ethernet

n

r

otr d

dPP

=


How to detect Collisions?

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� WLANs operate in the following unlicensed bands (US)– 2400 – 2483.5 MHz (2.4 GHz), 5150 – 5250 MHz (lower U-NII), 5250 – 5350

MHz (mid U-NII), and 5725 – 5825 MHz (upper U-NII)

� interference common !

� IEEE Standards operating in these bands include:– 802.11{b,g} in the 2.4 GHz band; 802.11a in the U-NII band

– 802.15 WPAN (Bluetooth) in the 2.4 GHz band

– 802.16 WirelessHUMAN in the mid and upper U-NII bands

� Other devices that also use these bands:– Field disturbance sensors, cordless telephones, low power devices, and

microwave ovens

– Non-802.11 Part 15 devices: cordless telephones, A/V repeaters, security cameras, baby monitors, & digital data links

� Licensed services that operate in these bands include:– Amateur radio in the 2.4 GHz and upper U-NII bands; fixed microwave in the 2.4

GHz band; and satellite in the lower U-NII band


Spectrum Usage

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Phone on

TCP download from a 802.11 AP

Performance worsens when there are large number of short-range radios in the vicinity

Panasonic 2.4GHz Spread Spectrum Phone 5 m and 1 wall from receiver

802.11 in presence of BT


Interference Problem

How to detect and characterise

external interference?

How to detect and characterise

external interference?

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Overview


– Introduction




– Introduction





� Conclusion

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Multi-Channel WLAN Meshes

Single-Radio Single-Channel

� Key Issue– MRN need to relay traffic AND serve attached clients

– In single radio WMNs, clients and MRNs operate on same channel

• more MRNs� more relay traffic, less user capacity, higher delay/jitter

• One large collision domain

Internet

MRN1 MRN2 MRN3 MRN4

Single radio (e.g. 802.11b) for backhaul and client access

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2 3 4 5 7 8 91 1110

RTS RTS

CTSCTS

6

2 packets in flight! Only 4 out of 11 nodes are active….2 packets in flight! Only 4 out of 11 nodes are active….

Backoff window doubles!

RTS RTS RTS


Multihop Causes More Collisions for Single Channel

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Single-Radio Single-Channel Mesh Throughput

Key issues:� Cannot Tx and

Rx in parallel (single radio)

� More problems due to collisions (hidden nodes) and interference

� Need to serialize reception and transmission

� Reduces capacity

Key issues:� Cannot Tx and

Rx in parallel (single radio)

� More problems due to collisions (hidden nodes) and interference

� Need to serialize reception and transmission

� Reduces capacity

Per MN Capacity=1/N , (N=hops)Per MN Capacity=1/N , (N=hops)

P1

P2

P3

P4

Step = 3

Step = 6

Step = 9

Step = 12

Single Radio Throughput (Best Case)

02468

1012141618202224

1 3 5 7 9Hops

Ava

ilabl

e B

andw

idth

(M

bps)

802.11b802.11a

Single Radio and Single Channel �� 12 Steps to send 4 packets

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Dual Radio WMNs

� Dual-radio mesh– Client access and backhaul traffic on two different Radios

• Different frequencies (e.g. 2.4 GHz 802.11b and 5 GHz 802.11a)

• Local access not affected by backhaul traffic � full speed

– BUT: Wireless Backhaul still shared � All 802.11a MRNs operate on same channel

• Reduced system capacity with growing network

VoIP service performance optimization in pre-IEEE 802.11s Wireless Mesh Networks, Nico Bayer, Marcel Cavalcanti de Castro, Peter Dely, Andreas Kassler, Yevgeni Koucheryavy, Piotr Mitoraj and Dirk Staehle, in: Proceedings of the IEEE ICCSC 2008, Shanghai, China, May 26-28 2008.

VoIP

background

VoIP

background

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Multi- Channel Mesh Backhaul

Key Idea:� Multi-radio, multi-

channel Backhaul required for Carrier-Grade

� Send and receive in parallel on different channels

� Channel qualities and traffic demand vary over time, unknown a priori

� How to find the “best”channel for given link?

� How to coordinate which channel to use between what nodes at a given time?

Two Radios and Multiple Channels �� 6 Steps to send 4 packets

P2

P3

P4

Step = 3

Step = 4

Step = 5

Step = 6

P1

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Exploit Diversity- Multiple Channels

Today’s US Spectrum Map – 300 MHz to 30 GHz� Utilizing multiple channels in backhaul

Goal: Assign n non-interfering

channels to n pair of nodes such that

n packet transmissions can occur

simultaneously

Goal: Assign n non-interfering

channels to n pair of nodes such that

n packet transmissions can occur

simultaneously

20 MHz

Single

Channel

Multiple

Channels

Single

RadioAvailable ☺

Multiple

RadioN.A. ☺

http://www.ntia.doc.gov/osmhome/allochrt.pdf

Large number of channels (spectrum) available

Large number of channels (spectrum) available

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Multi- Channel Mesh Backhaul

� With sufficient radios and sufficient channels, interference can be completely eliminated.

� For two nodes to

communicate they need

to share a common

channel

� Channel assignment becomes crucial and influences topology

Single Channel

deferX

Internet

4 Channels

2 Radios

Internet

3

3

2

24

41

1

RoutingRouting

Channel Assignment

Channel Assignment

Influencesinterference

Influences Topology andCapacity

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Channel Separation

5210

Non-overlapping channels, A = 1, B = 6Partially Overlapped Channels, A = 1, B = 3Partially Overlapped Channels, A = 1, B = 2

Same channel, A = 1, B = 1

LEGEND

3

4

5

6

0 10 20 30 40 50 60

Distance (meters)U

DP

Thr

ough

put (

Mbp

s)

Link A, Channel 1

Link B, Channel Y

Distance

(X-axis)ChSep = 0

ChSep = 1ChSep = 2

ChSep = 5

• For given channel distance there is a dedicated physical distance that maximizes throughput, can observe minimal distance

• This should depend on SNR and noise level

• Can be used for channel assignment if SNR, noise level known.

• Problem: Noise level depends on interfering traffic


Overlapping Channels Do Work for Single Radio

Banerjee-SIGMETRICS-2006

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Exploit Diversity- Multiple Channels

� Utilizing multiple channels in backhaul– Manageability:

• Different networks on different channels avoid interactions between networks

– Contention mitigation:

• Fewer nodes on a channel reduces MAC layer contention

– Better performance via use of more spectrum

How to best utilize multiple channelsin an Mesh network

with limited hardware?

How to best utilize multiple channelsin an Mesh network

with limited hardware?

W

m= # Radios

c = # Channels

w= per channel datarate

1

c

1

m

1

m m

m+1

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Multi-Radio, Multi-Channel Capacity

Observations:

� network density increases� per node capacity decreases– Use more channels shall be beneficial for dense networks

– BUT: Cannot add infinite number of radios

– What improvements are there when adding more channels?

– How many radios are then needed?

� General capacity constraints– Available spectrum bandwidth

– Connectivity constraints [Gupta-Kumar]• Availability of route places constraint on transmission power

– Interference constraints [Gupta-Kumar]• Limits spatial reuse among simultanous transmissions

How does the network capacity scale with

large number of channels, given m<c?

How does the network capacity scale with

large number of channels, given m<c?

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Multi-Radio, Multi-Channel Capacity

� Capacity constraints specific for c<m– Interface constraint [Kyasanur-Vaidya]

• Throughput is limited by number of Radios in a neighborhood of n nodes

– Destination bottleneck constraint [Kyasanur-Vaidya]• Node may be destination of multiple flows

• Per node throughput shared by all incoming flows

total throughput ≤ n * m * Wtotal throughput ≤ n * m * W

1

m

1

m

1

c

m

m+1

f flows

Node throughput T ≤ m*W

Per-flow throughput = T / f

Node throughput T ≤ m*W

Per-flow throughput = T / f

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Conflict Graph

� Conflict Graph– captures link interference between pair of links, which

• changes dynamically and with nodes entering and leaving

– Helps in • capacity estimation, routing, channel assignment, power management

– Can use weight to model fractional interference and variable traffic

� Conflict Graph requires knowledge of – packet transmission from nodes that are not “visible”– physical location of nodes within the network– whether or not multiple transmissions increase or decrease interference

1 2

64 5

3 1 - 4

1 - 2

2 - 3

4 - 5

2 - 5

3 - 6

5 - 6

Protocol Model vs.Interference Model

Protocol Model vs.Interference Model

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Conflict Graph

Connectivity Graph:

1 2

64 5

3

Ch=1 Ch=6 Ch=11

1 2

64 5

31 - 4

1 - 2

2 - 3

4 - 5

2 - 5

3 - 6

5 - 6

Conflict Graph:

[Subramanian08]

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Multi-Channel, Single-Radio


� Radio Card can switch channels dynamically– Today: ~2 ms with optimisations

– Possible: 80 microsec

� Centralized Channel Assignment: Compute channel assignments using global knowledge � Hard!

� Distributed: Use a modified RTS/CTS sequence to negotiate channels– RTS: Potential channels to be used

– CTS: Receiver tells sender which channel to use

� Problem: – How does the sender know which channel the receiver is listening on?

� Solutions mostly based on MAC layer extensions– Receive on all channels simultaneously � costly

– Negotiate channel before transmission � MMAC

– Use a synchronized hopping protocol � SSCH

– Use dedicated control radio and Common Control Channel � later

Single

Channel

Multiple

Channels

Single

RadioAvailable ?

Multiple

RadioN.A. ?

Single

Channel

Multiple

Channels

Single

RadioAvailable ?

Multiple

RadioN.A. ?

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Dedicated Control Channel

Negotiating Channel with RTS / CTS

Before starting, Node C sends RTS on Control Channel C1 to D including list of potential channels to be used. Node D replies with channel selected.

Nodes tune to the selected channel

B C D E G H IA KJ

RTS (C1,C3,C7) RTS (C3,C5,C7,C11)

CTS (C11)CTS (C3)

F

C2 C2C3 C11 C1

10 nodes are active, 5 packets in flight, 150% improvement! 10 nodes are active, 5 packets in flight, 150% improvement!

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Multi-Channel Hidden Terminal Problem

Let C1 be the control channel, single radio

C can hear traffic on C11 only, doesn’t hear the CTS from B consequently doesn’t know anything about traffic on C6 (D is too far to hear anything from B)

C1

C1

C11

RTS

RTSData

on

C6

Data on C6Data on C6

Collision

CTS (C6)

CTS (C6)

Tim

e

C6 C

1C

6

C6

C6

C1

A B C D

Possible solution: Use multiple radios

So-MobiHoc-2004

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More Problems

B does not hear the RTS from A on C1. As node B has its interface on C11 it doesn’t hear the RTS from A. Also, A cannot sense the carrier as it is on different channel. A falsely concludes that B is not reachable.

A B C

C1

C11

C11

RTS

Tim

e

RTS

Deafness ProblemDeafness Problem

A B

CD

Channel DeadlockChannel Deadlock

C1

C2

C3

C4

All nodes send RTS in circular fashion to neighbors. Deadlock may be resolved but system capacity is degraded.

Deafness ProblemDeafness Problem Channel DeadlockChannel Deadlock

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Multi-Channel, Multi-Radio

Observations

� Can apply single radio solutions to multi-radio

– number of channels typically greater than the number of radios

� Single radio solutions are more power efficient

– but power is not the primary concern in most mesh networks

� Single radio solutions are less costly than multi-radio solutions

– but radios are fairly inexpensive

– However, cannot add radios at will

– How many cards give a good speedup at a reasonable cost?

� Switching speed is a problem in single radio solutions

– but switching speeds are being reduced

� When distance between nodes is large, can use partially overlapping channels

� No Need to implement MAC Co-ordination mechanisms for concurrent transmissions

– Nodes can send and recieve in parallel using different Radios

– Several links can operate in parallel at different nodes

Single

Channel

Multiple

Channels

Single

RadioAvailable ?

Multiple

RadioN.A. ?

Single

Channel

Multiple

Channels

Single

RadioAvailable ?

Multiple

RadioN.A. ?

1 2

64 5

3

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Issues in Multi Radio WMNs

� Multi-radio backhaul mesh �use multiple channels/radios for backhaul– Example: MeshDynamics MD4000

� Compatibility options1. Use standard 802.11-based hardware

(BUT: need multiple interfaces).2. Use 802.11, but customized hardware.3. Develop minor extensions to 802.11 (AKA layer 2.5)4. Design new MAC protocol.

� Observations– Interface can only use a given channel at a time– For two nodes to communicate they need to

share acommon channel– Using multiple Radios, deafness, multi-channel hidden terminal and channel

deadlock problems can be mitigated– Channel re-assignments might be required to improve capacity, minimize

interference from external networks, etc– Network Partition Problems might arise

Network poorly connected

A B C

D

1,3

2,4

1,2 3,4

A B C

D

1,3

2,4

1,2 3,4

1,2

Some channels not used

A B C

D 1,2

1,21,2 1,2

A B C

D 1,2

1,21,2A B C

D 1,2

1,21,2

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Interference in Multi Radio WMNs

� Question: Do we still get improvement if we use 2 radios or more on Overlapping channels?

Channel X

TCP

Channel Y

TCP

15 cm Distance

A B

C D

0

5

10

15

20

25

30

35

64,64 60,64 56,64 52,64Channels

Thr

ough

put (

Mb/

sec)

Netgear: A to B Hop

Netgear: C to D Hop

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

Hop1 = A, Hop2 = G Hop1 = G, Hop2 = A

TC

P T

hrou

ghpu

t (M

b/S

ec)

Hop 2

Hop 1

Same channel or channel separation of 1 causes 46% - 49% reduction in overall throughput

802.11a link causes a 22% reduction in overall throughput, and a 63% reduction in throughput on the 802.11g link.

Interference is significant, RF hardware shielding work is beneficialInterference is significant, RF hardware shielding work is beneficial

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• In 802.11a, adjacent channels are not orthogonal.• High interference among adjacent channels:

• Hardware design: board crosstalk and radiation leakage • ACI due to overlapping spectrum masks and imperfect TX mask• Performance also impacted by modulation scheme, antenna distance, link quality


Overlapping Channels For Multi-Radio impose ACI

Norm

alized

Throughput Link

A-B

Channel Separation (20R-20T)

Ch. 36 Ch. 40

A B C

d’

36 40 44 48 52 56 60 64

36 52% 53% 48% 100% 100% 97% 100% 100%

40 41% 51% 46% 100% 100% 100% 100% 100%

44 60% 32% 52% 35% 55% 91% 99% 100%

48 99% 55% 44% 52% 41% 51% 99% 100%

52 100% 100% 75% 43% 51% 29% 100% 100%

56 100% 100% 100% 58% 35% 51% 48% 63%

60 100% 100% 100% 100% 46% 49% 52% 46%

64 100% 99% 98% 99% 50% 52% 38% 52%

Channel Link A-B

Ch

ann

el L

ink

B-C

36 40 44 48 52 56 60 64

36 51% 45% 97% 96% 96% 95% 96% 95%

40 36% 51% 41% 96% 96% 96% 96% 97%

44 95% 33% 50% 23% 43% 75% 94% 84%

48 99% 38% 26% 49% 33% 53% 96% 95%

52 100% 44% 95% 31% 50% 36% 96% 96%

56 99% 42% 96% 94% 34% 50% 39% 94%

60 100% 89% 96% 96% 36% 44% 50% 37%

64 97% 95% 88% 95% 51% 37% 38% 50%

Channel Link A-B

Ch

ann

el L

ink

B-C

36 40 44 48 52 56 60 64

36 49% 34% 42% 72% 45% 49% 53% 65%

40 45% 51% 43% 86% 59% 66% 57% 82%

44 43% 33% 51% 45% 43% 42% 47% 51%

48 58% 34% 50% 51% 50% 44% 59% 44%

52 65% 38% 40% 46% 51% 42% 43% 45%

56 48% 35% 44% 45% 44% 51% 49% 45%

60 100% 86% 99% 100% 99% 45% 50% 47%

64 96% 90% 96% 96% 96% 88% 28% 51%

Channel Link A-B

Ch

ann

el L

ink

B-C

[Kas10a, Kas10b]

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Overview


– Introduction




– Introduction





� Conclusion

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Multiple Radios – Channel Assignment Issues

� How should we assign channels to each interface? – Connectivity, Spectrum Utilization, Load Awareness, External Interference?

� Which interface should we send the packet on?– Routing determines traffic load on the virtual links

– Need to consider channel, range, data rate diversity.

� Potential Problems– Network Partition Problem

– Channel Dependency � Ripple Effect � Channel Re-assignment potentially needs Coordination

– Topology Change � Routing should be aware of Re-assignment

– Non-Convergent behaviour during Channel Re-assignment

Connectivity Optimal CapacityConnectivity Optimal Capacity

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Multiple Radios – Channel Assignment Issues

� Channel asignment strategies for the radios– Classification according to the timescale where channels are re-

assigned

– Static Interface Assignment• One channel per radio all the time

– (Semi)Dynamic Interface Assignment• Channels assigned dynamically (e.g. every 5 minutes) to match traffic

patterns and/or to reduce internal or external interference.

• Interference patterns can change, network may get disconnected

– Hybrid Interface Assignment• One channel to one radio for all time

– Channel might change on large timescale according to traffic demand

• for all other radios, channels are assigned dynamically to match traffic patterns and/or reduce interference.

• Most flexible.

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Multiple Radios – Static Interface Assignment

� Characteristics for Static Interface Assignment– A given interface fixed to a given channel

– E.g. C1 assigned to Radio 1, C2 to Radio 2, etc.

• Benefit: no dynamic coordination needed, stable connectivity, better survivability

– All nodes use common set of channels � used by Mesh Connectivity Layer [Draves04] or MUP

• Drawback: cannot use all channels, cannot consider traffic load

11

1

1

11

11

1

1

11

11

11

1

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Multiple Radios – Static Interface Assignment

� Different Approaches, also using diverse set of channels– [Marina-05]Treat Channel Assignment as Topology Control Problem,

– use conflict graph to model interference

– Assign Channels to minimize maximum conflict weight

– [DAS05] Use ILP to maximize # concurrent transmissions given connectivity constraints

– [Tang05] Statically bind interface/channels by minimizing interference among links

Ch 2,3

�Drawback: longer routes required

�Mostly Centralized Approaches

60

522

1

64

60

Not possible

52

56

52

60

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Multiple Radios – Semi Dynamic Interface Assignment

� Characteristics for Semi Dynamic Interface Assignment– Re-Assign channels at slow time scales

– External Interference Aware, Centralized � [Ramachandran06]

– Load Awareness

– Centralized [Raniwala04]

– Distributed [Raniwala05]

Ch 2,3

� Drawback: longer routes required

60

522

1

64

60

Not possible

52

56

52

60

2 radios / node, 4 channels

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Load-Aware Channel Assignment

10 50 40 10 50 40

Which channel

assignment

is better?

Which channel

assignment

is better?

� How to develop traffic-aware channel assignment algorithms?

� How to estimate traffic that varies over time?

� How to estimate the interference graph?

� How to handle non-binary interference through RSS variation?

� How much does traffic-awareness improve network performance and when is it beneficial?

� How to develop traffic-aware channel assignment algorithms?

� How to estimate traffic that varies over time?

� How to estimate the interference graph?

� How to handle non-binary interference through RSS variation?

� How much does traffic-awareness improve network performance and when is it beneficial?

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Multiple Radios – Dynamic Interface Assignment

� Characteristics for Dynamic Interface Assignment– Interface can switch channel when needed [So-MobiHoc-2004 , Bahl04]

• Any channel can be used at any given time

• All Methods for Single-Radio Multiple-Channels can be used (SSCH, MMAC, ...)

• Benefit: no limitations on channel usage

• Drawback: coordination required, deafness problem

Ch 6 Ch 11

11

1

1

11

11

1

1

11

11

11

1

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Multiple Radios – Hybrid Interface Assignment

� Common Control Channel [e.g. Jain01]– One common control channel (e.g. On radio 1), many data channels

(switchable, e.g. on radio 2)

– Control channel used to negotiate, which data channel to use

– Example: DCA Protocol by Wu and Tseng (2000) using RTS/CTS/RES

– Advantages:• All nodes aware of busy channels

• No need for time synchronisation

– Disadvantages• Nodes contend for control channel � Increased cost due to dedicated channel for

control (Bottleneck), but several approaches how to reduce the problem

• When few channels available, spectrum efficiency is low

Control Channel: 1 Control Channel: 1

Data Channel: 2-4 Data Channel: 2-4

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� Hybrid Interface Assignment: Fixed/Switchable Approach � Net-X� Each node has at least 1 fixed, 1 switch-able interface

� Connectivity is maintained, all channels used

� Every node picks a channel as it’s fixed channel

� Different nodes use different fixed channels

� Once a “connection” is made, there may not be a reason to switch channels again for that particular flow � Per Channel Packet Queue

AFixed (ch 1)

SwitchableA

Fixed (ch 1)

SwitchableB

Fixed (ch 2)

SwitchableB

Fixed (ch 2)

SwitchableC

Fixed (ch 3)

SwitchableC

Fixed (ch 3)

Switchable12 3 2

B

D

C

Ch. 3

Ch. 4

ACh. 1 B

D

C

Ch. 3

Ch. 4

ACh. 1

Packet to D

Packet to C

Ch. 4

Ch. 3

Packet to C arrives

buffer packet

Interface switches

to channel 3

[Kyasanur06]

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� Hybrid Interface Assignment: Fixed/Switchable Approach � Net-X� Multi-channel broadcast support, Scheduling for channel switching

� Hybrid Multichannel Control Protocol (HMCP)

� Challenge: Create and maintain channel diversity

� Fixed Channel Selection Protocol � Semi Dynamic� On startup each node picks a random fixed channel

� Periodically send a “hello” pkt. containing fixed channel & 1-hop neighbors info. on all channels (using the switchable interface) � High Overhead

� Maintain a NeighborTable containing fixed channels being used by neighbors

� Select the channel with fewest nodes as a candidate � Not traffic aware!

� Change fixed channel to candidate channel probabilistically to avoid oscillations

AFixed (ch 1)

SwitchableA

Fixed (ch 1)

SwitchableB

Fixed (ch 2)

SwitchableB

Fixed (ch 2)

SwitchableC

Fixed (ch 3)

SwitchableC

Fixed (ch 3)

Switchable12 3 2

B

D

C

Ch. 3

Ch. 4

ACh. 1 B

D

C

Ch. 3

Ch. 4

ACh. 1

[Kyasanur06]

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KAUMesh

� KAUMesh

– Based on Net-X, Linux 2.6, Cambria Platform (Gateworks)

– Three 802.11a radios per mesh node (m = 2), Legacy clients with 1 radio 802.11b/g

– Nagios Network Management Platform http://www.cs.kau.se/cs/prtp/pmwiki/pmwiki.php?n=Resources.MeshTestbedhttp://www.cs.kau.se/cs/prtp/pmwiki/pmwiki.php?n=Resources.MeshTestbed

Multi-Channel Routing,

Hybrid Channel Assignment

Interface and ChannelAbstraction Layer, Aggregation

IP Stack

QoS InterfaceDevice Driver

User Applications

ARP

QoS InterfaceDevice Driver

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Multiple Radios – Routing Issues

� In Multi-Channel– Select routes that have channel diversity � new routing metrics such as WCETT

� Need to consider Switching Cost– Switching interfaces results in packets being queued and delayed

– If a node is on more routes, might require more switching

– Try to minimize the amount of switching while maximizing channel diversity– Broadcast packets need to be sent on all channels requiring frequent switching

2 1

2 1

Which Route is better?

A-B-D or A-C-D?

3

A

B

DC

E

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Multiple Radios – Routing

� Can we do better than single path? can use any path in the mesh– To reduce channel switch latency, to balance the load

– To cope with temporary interference

� Having multiple paths available, path selection becomes packet scheduling problem– Braided Routing sends on many paths in parallel

– Anypath [Lav10] can compose individual path segments dynamically• Take into account switching cost �

send to neighbor which has a good enough path while minimizing local switching cost

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Overview


– Introduction




– Introduction





� Conclusion

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Spectrum Allocation

Static Licensing

� Today: Static Licensing� Benefits: Can control Interference, simple hardware

� Drawback: Only small portion of spectrum available, inflexible

Source: FCC

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Spectrum Allocation

Fixed Spectrum Allocation - Conclusion

� Static allocation of spectrum is inefficient– Slow, expensive process that cannot keep up with technology

� In need for spectrum allocation rules that encourage innovation & efficiency– Free markets for spectrum, more unlicensed bands, etc.

� WLAN spectrum is congested– E.g. large cities like London, Singapore

– Unlicensed systems need to scale and manage user “QoS”

� Density of wireless devices will continue to increase– ~100x with sensors/pervasive computing

� Interoperability between radio standards required– Programmable radios that can form cooperating networks across multiple PHY’s

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Spectrum Allocation

Dynamic Spectrum Allocation

� Tomorrow: Dynamic Spectrum Allocation� Dynamic Spectrum Allocation Networks

� E.g. in US: xG Initiative

� Idea: allow unlicensed users access to licensed bands → increase spectral efficiency

� Requirement: Need to evaluate spectrum occupancy in order to identify suitable frequency bands

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Spectrum Allocation

Fixed Spectrum Allocation - Utilization

� Uneven Spectrum Utilization - Measurement Results� Varying utilisation across frequencies

� Utilisation for given band varies over time and place

Am

plitu

de (

dBm

)

54% 35% 7%

Frequency (GHz)

sparse

medium

heavy

0.25% 0.12% 4.6%Utilization (%) Source:Shared Spectrum Company

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Cognitive Radio

System Evolution

Fixed Standardised

Platforms

Fixed Standardised

Platforms

Multi-Standard Platforms


SDR based

Platform

SDR based

Platform

CognitiveRadio

Platform

CognitiveRadio

Platform

� Software Defined Radio (see SDR Forum)– Collection of hard- and software modules which allow to build highly flexible and

configurable systems for wireless networks and mobile radio platforms

– Radio is software programmable, dynamically adjustable, etc.

– Architectural complexity is challenging

– Different degrees of “Software”:

• Fully programmable platform based on CPU, RF Frontend, A/D converters �Microsofts SoRa GNURadio, etc.

• Programmable multistandard platforms

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Cognitive Radio

System Evolution

Fixed Standardised

Platforms

Fixed Standardised

Platforms



SDR based

Platform

SDR based

Platform

CognitiveRadio

Platform

CognitiveRadio

Platform

� Cognitive Radio (J. Mitola , 1999)– a radio that is

• aware of and can sense its environment (Spectrum Sensing)

• Obtain knowledge of spectrum usage (location and time)

• Apply Rules of sharing available resources (time, frequency, space)

• Embedded intelligence to adjust its operation according to (Dynamic Spectrum Selection, Adaptive Modulation, Adaptive Power Control, Real-Time Spectrum Mgmt.)

• some objective function, e.g.

– highly reliable communications whenever and wherever needed;

– efficient utilization of the radio spectrum

A cognitive radio can autonomously change its transmitting parameters based on the

interactions with the environment in which it operates.

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Cognitive Radio

Cognitive Radio Cycle

OBSERVE-ORIENT-DECIDE-ACT

External Intelligence Sources

OrientEstablish Priority

PlanNormal

Generate Alternatives(Program Generation)Evaluate Alternatives

Register to Current Time

DecideAlternate Resources

Initiate Process(es)(Isochronism Is Key)

Act

Learn

Save Global States

Set DisplaySend a Message

ObserveReceive a Message

Read Buttons

OutsideWorld

NewStates

The Cognition Cycle [Mitola99]

PriorStates

Pre-process

Parse

ImmediateUrgent

Infer on Context Hierarchy

•Signal detection/classification•GPS Location, time•Network•Others’ observations•Device sensors•User interfaces

•Signal detection/classification•GPS Location, time•Network•Others’ observations•Device sensors•User interfaces

Hypotheses testing using e.g.•Data mining•Hidden Markov Models•Neural Nets•Fuzzy Logic•Ontological Reasoning

Hypotheses testing using e.g.•Data mining•Hidden Markov Models•Neural Nets•Fuzzy Logic•Ontological Reasoning

Map believes about networkstate to an adaptation, guided by radio goal, constrained by policy•Genetic algorithms•Simulated annealing•Local search•Case based reasoning

Map believes about networkstate to an adaptation, guided by radio goal, constrained by policy•Genetic algorithms•Simulated annealing•Local search•Case based reasoning

Refine hypotheses and models•Data mining•Hidden Markov Models•Neural Nets•Fuzzy Logic•Ontological Reasoning•Case based learning•Bayesian learning

Refine hypotheses and models•Data mining•Hidden Markov Models•Neural Nets•Fuzzy Logic•Ontological Reasoning•Case based learning•Bayesian learning

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Cognitive Radio

Cognitive Network

� Problems with CR– Real World: Interaction of numerous cognitive radios � Adaptations create more

adaptations � Infinite Loops with growing network size possible

– Even for simple algorithms, ensuring convergence and stability will be nontrivial

– Example: Distributed SINR maximizing power control in a single cluster

• Increase TXPower to increase in interference� all nodes will transmit at max

� Cognitive Network– a network that has a cognitive process that perceives current

network conditions, and then plans, decides, and acts.

– The network can learn from these adaptations and use them to make future decisions, all while taking into account end-to-end goals.

– Can be composed of Cognitive Radios but requires coordination and distributed operation

– Typically features a distributed knowledge plane that conveys information between cognitive nodes in a scalable way

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Dynamic Spectrum Access (DSA)

Definition

� Dynamic Spectrum Access (DSA)– Different Spectrum Usage Policy:

• Licensed (Primary Users, PU) and

• Unlicensed Users (Secondary Users, SU)

– SU sense for unused spectrum bands and try to use those

• Opportunistically or

• In cooperation with the primary user

• Coordinated DSA: using spectrum servers or micro-auctions, etc

– Challenge: reliable detection of vacant frequency/width in time and space

• Cooperative spectrum sensing has been proposed to cope with fading and shadowing effects.

• Static Databases as a current FCC/IEEE802.22 solution

– Coexistence:

• if PU is absent, SUs can use frequency, if they do not harm others.

• SUs need to vacate spectrum portion once PU detected � difficult in practice

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Pow

er

Frequency

PU1

PU2

PU4

PU3


Opportunistic Spectrum Use

� Sense the spectrum over a wide bandwidth � difficult� Identify Spectrum Hole � difficult� Transmit in Spectrum Hole � Detect if primary user appears � Move to new Spectrum Hole� Adapt bandwidth, power, modulation to meet requirements

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Cognitive Radio as Enabler

Time

Frequency

Power

Spectrum Hole� White Space

Used Spectrum

� Cognitive Radio is Key to Dynamic Spectrum Access (DSA)– CRs can exploit temporarily unused spectrum portions � Spectrum Holes or

White Spaces � TV-bands as example (IEEE802.22)

– CR nodes change transmission parameters on the fly to avoid interference

• Transmission power, modulation scheme, etc

– DSA allow Cognitive Radios to operate in best available channel

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Challenges

� Hidden terminal problem in TV bands

– Cannot sense the transmitter but still might interfere

– Detecting potential interference with licensed receiver is HARD

518 – 524 MHz

TV Coverage Area

521 MHz interference

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Challenges

� Maximize use of fragmented spectrum

– Available Spectrum portion could be of different widths

– Coordinate spectrum availability among nodes

Pow

er

Frequency

PU1

PU2

PU4

PU3

Sig

nal S

tren

gth

FrequencyFrequency

Sig

nal S

tren

gth

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Cognitive Radio Ad-Hoc Networks

System Model

An existing network infrastructure which has an access right to a certain spectrum band. E.G. GSM, Analog TV, etc

Primary User has a license to operate in a certain spectrum band.PUs do not need any modification or additional functions for co-existence with CR users

Does not have license to operate in a desired band.Spectrum access is allowed only in an opportunistic manner.

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System Model with learning capabilities

User

CMN

CMN CMN

CMN

Gateway CMN

1. Observe and

Orient

2a. Decide and Act

2b. Coordinate and

Cooperate

3. Learn

4. Adapt

InternetA cognitive radio Ad-Hoc network is composed of cooperative CR-nodes which

ideally coordinate their operation

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CRAHN Architecture

� Spectrum Awareness– Can be implemented by a Spectrum Manager within each nodes

Radio

Environment

Spectrum

Sensing

Spectrum

Sensing

Spectrum

Decision

Spectrum

Decision

Spectrum

Mobility

Spectrum

Mobility

Spectrum

Sharing

Spectrum

Sharing

Transmitted signal

Spectrum Characterization

RF Stimuli

PN Detection / Load Estimation

Spectrum Selection

Spectrum Handoff

Spectrum Selection

Determine which portions of the spectrum is available and detect the presence of licensed users when a user operates in a licensed band

Select best channel and widthCoordinate Access with other users and determine PHY/MAC parameters such as transmit power, modulation scheme, etc.

Once PU detected, decide to vacate the spectrum, select next frequency portion

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CRAHN Spectrum Management Framework

[Akyildiz09]

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Overview


– Introduction




– Introduction





� Conclusion

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CRAHN Architecture

� Spectrum Awareness– Detect spectrum holes by the CR so that it can adapt itself to its

environment

Radio

Environment

Spectrum

Sensing

Spectrum

Sensing

Spectrum

Decision

Spectrum

Decision

Spectrum

Mobility

Spectrum

Mobility

Spectrum

Sharing

Spectrum

Sharing

Transmitted signal


RF Stimuli


Spectrum Selection

Spectrum Handoff

Spectrum Selection

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Spectrum Sensing

Spectrum Sensing Methods

� Spectrum Sensing– Typically implemented by a Spectrum Manager within each node

– PU Detection: based on RF Observation, decide if PU present or not

– Cooperation: Exchange sensing information with neighbors for better detection possibility

– Sensing Control: Adapt sensing parameters (frequency portion, width, duration, ...) dynamically to RF Spectrum. Coordinate operations with neighbors

Link Layer

PHY Layer

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Spectrum Sensing

Spectrum Sensing Methods

� Energy detection

� reduced amount of prior signal knowledge required

� relative computational simplicity

� universal applicability

� Spectrum Sensing– Detect spectrum holes by the CR so that it can adapt itself to its environment

sensing

Transmitterdetection

CooperativeSensing

Interference-Based

detection

Matched filtering Energy

Cyclo stationary

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Spectrum Sensing

Measurement Location and Antennas

Location had excellent line-of-sight to NYC

LPA antenna 1000-3000 MHz Discone antenna 30-1000 MHz

[Data from SharedSpectrum.com report]

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Spectrum Sensing

High Utilization (Public Safety Band)

High Bandwidth, Spread Spectrum Signal

Upper Bound (Frequency Resolution 65 MHz/501=130 kHz/bin) 50% Duty Cycle is too High, 19% Utilization Measured Using Small

Frequency Bins (450-455 MHz)

17% Duty Cycle


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Spectrum Sensing

UHF TV Band

Digital TV Analog TV

Transmitter Turned Off At Night

Upper Bound (Frequency Resolution 108 MHz/501=216 kHz/bin) [Data from SharedSpectrum.com report]

Dynamic Spectrum Sharing PossibilitiesDynamic Spectrum Sharing Possibilities

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Spectrum Sensing

NYC Spectrum Occupancy Summary

13% Average Duty Cycle

� All Bands 30 MHz to 3000 MHz

� Two 24 hour periods

� Peak Usage Period – Political Convention

Start Freq

(MHz)

Stop Freq

(MHz)

Bandwidth

(MHz) Allocation

Average Duty

Cycle (Day 1)

Average Duty

Cycle (Day 2)

Average

Duty Cycle

Occupied

Spectrum (MHz)

Net Average

Duty Cycle

1240 1300 60 Amateur 0.0003 0.0001 0.0002 0.0120

1525 1710 185

Mobile Satellite, GPS L1, Mobile Satellite,

Meteorologicial 0.0024 0.0013 0.0019 0.3423

225 406 181 Fixed Mobile, Aero, others 0.0053 0.0037 0.0045 0.8145

1400 1525 125 Space/Satellite, Fixed Mobile, Telemetry 0.0152 0.0005 0.0079 0.9813

1300 1400 100 Aero Radar, military 0.0216 0.0013 0.0115 1.1450

1990 2110 120 TV Aux 0.0191 0.0082 0.0137 1.6380

2110 2200 90

Common Carriers, Private Companies,

MDS 0.0182 0.0190 0.0186 1.6740

1710 1850 140 Fixed, Fixed Mobile 0.0235 0.0254 0.0245 3.4230

2686 2900 214 Surveillance Radar 0.0286 0.0309 0.0298 6.3665

960 1240 280 IFF, TACAN, GPS, others 0.0356 0.0408 0.0382 10.6960

108 138 30 Air traffic Control, Aero Nav 0.0527 0.0403 0.0465 1.3950

30 54 24 PLM, Amateur, others 0.0430 0.0625 0.0528 1.2660

2200 2300 100 Space Operation, Fixed 0.0527 0.0618 0.0573 5.7250

216 225 9 Maritime Mobile, Amateur, others 0.0586 0.0595 0.0591 0.5315

2360 2390 30 Telemetry 0.0620 0.0642 0.0631 1.8930

2500 2686 186 ITFS, MMDS 0.1043 0.1042 0.1043 19.3905

2390 2500 110 U-PCS, ISM (Unlicensed) 0.1347 0.1551 0.1449 15.9390

406 470 64

Amateur, Radio Geolocation, Fixed, Mobile,

Radiolocation 0.1661 0.1475 0.1568 10.0352

138 174 36 Fixed Mobile, amateur, others 0.1708 0.1698 0.1703 6.1308

2300 2360 60 Amateur, WCS, DARS 0.2022 0.2053 0.2038 12.2250

470 512 42 TV 14-20 0.2114 0.2100 0.2107 8.8494

902 928 26 Unlicensed 0.2227 0.2346 0.2287 5.9449

928 960 32 Paging, SMS, Fixed, BX Aux, and FMS 0.2364 0.2437 0.2401 7.6816

698 806 108 TV 52-69 0.2958 0.3079 0.3019 32.5998

1850 1990 140 PCS, Asyn, Iso 0.3309 0.3443 0.3376 47.2640

512 608 96 TV 21-36 0.3552 0.3427 0.3490 33.4992

608 698 90 TV 37-51 0.4616 0.4609 0.4613 41.5125

806 902 96 Cell phone and SMR 0.4619 0.4645 0.4632 44.4672

54 88 34 TV 2 -6, RC 0.5283 0.5208 0.5246 17.8347

174 216 42 TV 7-13 0.7773 0.7795 0.7784 32.6928

Total 2850 373.9696 0.1312

Low occupancy bands


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Spectrum Sensing

Low Utilization in a Rural Environment - WLAN


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Spectrum Sensing

Sensing Control

� In-Band Sensing: Periodical Transmission/Sensing cycle– Maximize channel efficiency while maintaining required detection probability

– Trade-off: Larger sensing time � better detection accuracy � lower throughput

– Possible to apply Re-inforcement based learning

� Out-of-Band Sensing: For spectrum mobility– Minimise spectrum discovery time

– Detecting better spectrum band might take longer sensing time

Sensing Control

Interference Avoidance

(In-Band Sensing)Fast Discovery

(Out-of-Band Sensing)

Sensing Order

(Which spectrum portion to sense first?)

Stopping Rule

(When to stop sensing?)

Sensing Time

(How long to sense the spectrum?)

Transmission Time

(How long to transmit data?)

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Spectrum Sensing

Cooperative Sensing

� Cooperative Sensing – CMNs exchange sensing information

� overhead

– Increased detection probability underfading and shadowing environments

– Want to minimise also false positive

– Which nodes to cooperate in exchanging sensing information ?

– Minimize control overhead/delay

– Sensing clusters: Nodes send sensing information to clusterheads, which decide outcome � Coalitional Game Theory

– Reliable control channel required to convey PU detection outcome. How?

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Spectrum Sensing

Cooperative Sensing

� Issues– Do you trust the reports? Do you trust the outcome?

– Sensing a frequency band consumes energy and time which may alternatively be used to data transmissions. What is the incentive to cooperate?

– Users have incentives to either not sense at all or to sense for a shorter duration then stipulated.

– Motivate users to perform cooperative sensing

� Forming Coalitions:– How are the coalitions formed?

– How do players arrive at equilibrium?

– What is the long term behavior of the coalition formation process?

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Spectrum Sensing

MAC Layer Sensing

� Sensing at MAC Layer?– A large number of channels have to be periodically sensed for the presence of PUs

– Support for QoS traffic requires delays as low as 20ms

– How can sensing meet these requirements?

� Two-stage spectrum sensing (TSS) mechanism– Stage 1: Fast sensing (e.g., energy detection)

• in band only, may or may not be scheduled

• Consolidated reports on the fast sensing outcome is sent to moderator

• Moderator determines the need for the next fine sensing and how much time is required

– Stage 2: Only if needed, perform fine sensing (e.g., feature detection)

Need to synchronize sensing time among CR nodesNeed to synchronize sensing time among CR nodes

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Overview


– Introduction




– Introduction





� Conclusion

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CRAHN Architecture

� Spectrum Decision– Based on outcome of sensing, decide best spectrum portion to use

Radio

Environment

Spectrum

Sensing

Spectrum

Sensing

Spectrum

Decision

Spectrum

Decision

Spectrum

Mobility

Spectrum

Mobility

Spectrum

Sharing

Spectrum

Sharing

Transmitted signal


RF Stimuli


Spectrum Selection

Spectrum Handoff

Spectrum Selection

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Spectrum Decision

� Spectrum Decision: 2 Stage Process– Step 1: Characterise the spectrum based on

• Sensed RF information

– Interference, Loss, Error Ratio

– Link layer delay due to e.g. Contention

• Information available from Primary Network

– Model and analyse Primary Network

– Predict behavior/traffic characteristics of PUs

– Step 2: Decide, which spectrum band(s) (center frequency, width) to select based on QoS requirements and spectrum characteristics

• Single Spectrum Decision

• Multi Spectrum Decision

– Each CR user selects multiple spectrum bands, possibly non-contiguous and use them in parallel

– Immune to interference and PU

– Lower power per spectrum band

Frequency

5Mhz20Mhz

PU

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Spectrum Decision

� Single Spectrum Decision – Each CR user select a single band based on QoS requirements

Sig

nal S

tren

gth

Frequency

Frequency

Sig

nal S

tren

gth

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Spectrum Decision

� Single Spectrum Decision – Each CR user select a single band based on QoS requirements

– E.g. MSRs Time Spectrum Block [Yuan07]

Time

Frequency

t t+¢t

f

f+¢f

Primary users

Neighboring nodes’time-spectrum blocks

Node’s TSB

AC

K

AC

K

AC

K

Time-Spectrum Block

Within a time-spectrum block, any MAC and/or communication protocol can be used

f+∆f

ft t+∆t

Dynamic Spectrum Assignmenttranslates to dynamic packing of TSBs into time, frequency and space

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Single Spectrum Decision: bSmart

Which TSB, how long, what channel width?– For given TSB, can estimate capacity.

– Given traffic demands, need to calculate feasible (take into account PUs), non-interfering spectrum allocation schedule � NP-complete even in single hop

– Idea: Assign each network flow blocks of bandwidth B/N, B = total spectrum, N = nr. Disjoint flows in interference range

– How long should we transmit??

• Observation: Long Blocks � Large Delays � less adaptivity

• Short Blocks � More overhead and congestion on Control channel

�Nodes always try to send for Upper bound Tmax

~10ms

� Distributed SpectruM Allocation oveR whiTe spaces– CMAC regulates which sender-receiver pair may reserve some TSB– Dynamic spectrum allocation algorithm which decides what block is actually

reserved

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Single Spectrum Decision: bSmart

� Distributed SpectruM Allocation oveR whiTe spaces– CMAC regulates which sender-receiver pair may reserve some TSB– Dynamic spectrum allocation algorithm which decides what block is actually

reserved

1. Find smallest bandwidth ∆b for which current queue-length is sufficient to fill block ∆b ∆Tmax

2. If ∆b ≥ B/N then ∆b := B/N

3. Find placement of ∆bx∆t blockthat minimizes finishing time and doesnot overlap with any other blocks and PUs

4. If no such block can be placed dueprohibited bands then ∆b := ∆b/2

Tmax

∆b=B/N

Tmax

∆b

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Routing Issues

� Routing in CRAHNs is similar to Classical MANET/Mesh but:– Topology changes due to PU activity

– Several links fail at a time due to PU activity� Correlated link availabilities

– available spectrum is location-dependent � heterogeneous across the network

– Route Stability becomes an Issue

– Spectrum aware routing � route around PU area (longer path) or invoke spectrum handoff?

� Rerouting:– Link-Switching: One or more links must be replaced by others not blocked by

Pus � still E2E path available????

– Channel Switching: A link must change spectrum portion (channel)

– New routing metrics needed!

– Multi-/any path approaches need to consider• dynamic spectrum availability

• imbalanced coexistence between PUs and SUs

SD

PU

PU

PUPU

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Spectrum Aware Routing

� Example: SPEAR [Samptah08]– Integrate spectrum discovery with route discovery

– Coordinate channel usage explicitly across nodes to optimize channel assignment on a per-flow basis, and to minimize inter-flow interference

– Exploit local spectrum heterogeneity and assign different channels to links on the same flow to minimize intra-flow interference.

– AODV style route discovery

• Accumulate PU channel information

• Allow multiple paths

• D selects best route and channels

• Embeds this in RREP

• Local adaptation to cope with PU �� Problem?

SD

PU ch= 1

PU ch=3

PU ch= 4PU ch = 2

3 4 3 2

SD

PU ch= 1

PU ch=3

PU ch= 4PU ch = 2

RREQ

RREQ

RREQ

Select route;Schedule Channel

Select route;Schedule Channel

RREQ: accumulate (nodeID, spectrum avail, link quality)

RREQ: accumulate (nodeID, spectrum avail, link quality)

RREP: selected node channel + slot schedule for TDMA

RREP: selected node channel + slot schedule for TDMA

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Spectrum Aware Multipath Routing

� Urban-X Routing [Kim2010]– Multipath Forwarding mesh composed out of active links, virtual links

– CETT routing metric uses estimates for per link PER based on PN traffic estimation, packet length, SINR and modulation scheme

– Extended AODV to create forwarding mesh using multiple next hop candidates

• Changed RREQ and RREP processing to create multiple next hop candidates

• Threshold for max path length

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Spectrum Aware Multipath Routing

� Urban-X Forwarding [Kim2010]– Decide for each packet which channel/next hop

– Adjust to congestion and external PN traffic

– Based on multi-channel backpressure

– Consider switching cost while maximizing network utility function

– Per channel queue

– Channel scheduler

L2.5

CH1

CH4

Xj,i

Routing Node j, CH4

Node k, CH1

CH7

c*=argMax Pc/R

j* =argMin Crate

dest Next hop CH_Q

Xi,j

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Spectrum Decision

� Open Issues – How to model and analyse characteristics of PU network correctly?

– A given network load may change over time. How to predict network user load changes over time?

– How to characterize and estimate CR radio channel so as to guesscorrectly QoS parameters such as throughput, PER, delay, etc?

– How to enforce certain QoS level using Admission Control?

– Once spectrum band (center frequency and width of spectrum) is decided, how to determine (jointly) parameters like sending power, modulation scheme, channel coding and higher layer reconfiguration (e.g. TCP timers or rerouting)

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Overview


– Introduction




– Introduction





� Conclusion

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CRAHN Architecture

� Spectrum Sharing– Maintain QoS of CR userswithout causing interference to PUs

– Adaptive allocation of Radio Ressources

Radio

Environment

Spectrum

Sensing

Spectrum

Sensing

Spectrum

Decision

Spectrum

Decision

Spectrum

Mobility

Spectrum

Mobility

Spectrum

Sharing

Spectrum

Sharing

Transmitted signal


RF Stimuli


Spectrum Selection

Spectrum Handoff

Spectrum Selection

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CRAHN Architecture

� Spectrum Sharing � MAC Layer– Regulate medium access by multiple parallel CR users

– Coordination is required to prevent collisions where spectrum portions overlap

� Problematic– How to cope with coexisting licensed PUs?

– How to deal with large spectrum portion?

� Approaches for Spectrum Sharing– Intra-Network

– Inter-Network

[Akyildiz09]

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Intra-Network Spectrum Sharing

� Centralized � Distributed– Coordinated

– Autonomous

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Inter-Network Spectrum Sharing

� Centralized � Distributed

� Spectrum Server can facilitate co-existence of heterogeneous radios by advising them on:– Interference information

– Spectrum etiquette

– Location specific services

– Many more things ….

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Example Spectrum Server: Channel Occupancy Database

http://whitespaces.msresearch.us

<primary user [ ], signal strength [ ] at location>

Static PU data(TV, MICs, etc)

Location

Terrain

Propagation Model

TV Band availability mirrors population density“Google for spectrum”“Google for spectrum”

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Spectrum Sharing Challenges

� Topology Discovery– May be difficult due to PU activity

� Spectrum Access and Coordination– C3 detects CR1 and CR2

– PU activity may lead CR1 to change spectrum during ongoing transmission

– May lead to lost opportunities

PU Activity on

Channel 3

PU Activity on

Channel 1, 2

CR can use

CH=3

CR can use

CH=1, 2

???

PU Activity

CR 1

CR 2

CR 3

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Common Control Channel

� Common Control Channel - CCC– CCC enables mutual observation between heterogeneous nodes to explicitly

coordinate spectrum usage

– Exchange of CCC messages by an extra narrow-band (low bit-rate) radio

– Periodically broadcast spectrum usage parameters to neighbors

– Enables distributed algorithms for spectrum co-existence

– In-Band CCC simplifiescoordination but leadsto low throughput

– Out-Band CCC usinglicensed channel mayrequire additional radio

[Ray08]

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Spectrum Sharing

� Common Control Channel: (e.g. in 900 MHz)– Contend for spectrum access on CCC

– Reserve time-spectrum block

– Can also leverage to exchange spectrum availability information

– Overhear neighbors control messages, store info.

– Neighbors can help in spectrum selection due to overhearing and better knowledge

� Example: CMAC (MSR) [Yuan07 ]– RTS: contains traffic load and proposal for

available TSBs to use

– CTS: receiver selects spectrum (freq, width, time)

– DTS: Data Transmission reServation

• Informs neighbors about reserved TSB

– Mechanisms to reduce control channel load

Sender Receiver

DATA

ACK

DATA

ACK

DATA

ACK

RTS

CTS

DTS

Waiting Time Tim

e-Spectrum

Block on R

adio 2

t

t+∆t

CC

C on R

adio 1

PHY Layer Carrier Sensing

No BACKOFF

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Spectrum Sharing Information Exchange

Control channelTime

The above depicts the following scenario1) Primary users (fragmentation)2) In multi-hop CRAHNs � neighbors have different views

Primary Users

Network Allocation Matrix: Nodes record info for reserved time-spectrum blocks

Fre

quen

cy

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Example Interactions – MSRs KNOWS platform

Coordinate spectrum

availability [YuanY07]

Maximize Spectrum

Utilization [Yuan07]

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Game-Theoretical Approaches

� Networks compete for the same medium– How to manage the interference in such competitive scenarios?

– How to efficiently share the spectrum?

– Spectrum sharing problem can be formulated as a game between entities

� Game Theory– Microeconomics and pricing based schemes for spectrum sharing, negotiation and

coexistence, Incentive mechanisms for cooperation

Movie ”A Beautiful Mind” inspired by the

Nobel Prize (Economics) winning

mathematician John Nash.

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Game-Theoretical Approaches

� Game Theory– Helps to formulate strategies and to understand situations in which players interact

– Player are considered rational and determine the best strategy for them

– Players may cooperate or not

– objective is to reach the Nash Equilibrium where no user can get utility benefit by changing its own allocation strategy alone

� Questions– Assume that all transmitters operate in a non-cooperative selfish manner:

• What are their optimal power allocation strategies across their carriers?

• Given any set of channel realization, is it possible to predict the outcome of the game? What is the Nash equilibrium of the game?

• If it exists, is it unique (i.e., are there many equilibria?)

• How close is the selfish distributed approach from the centralized approach?

– Can we benefit if players cooperate in a competitive market? • E.g. Forming coalitions for spectrum sensing

• Cooperation between CRs and PUs?

• Forming hierarchies should give better incentives� Stackelberg game

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Overview


– Introduction




– Introduction





� Conclusion

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CRAHN Architecture

� Spectrum Mobility– Exercised when current band becomes worse or PU is detected

Radio

Environment

Spectrum

Sensing

Spectrum

Sensing

Spectrum

Decision

Spectrum

Decision

Spectrum

Mobility

Spectrum

Mobility

Spectrum

Sharing

Spectrum

Sharing

Transmitted signal


RF Stimuli


Spectrum Selection

Spectrum Handoff

Spectrum Selection

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Spectrum Mobility

� Spectrum Mobility– Exercised when current band becomes worse or PU is detected

– Coordination mostly based on Common Control Channel

– May lead to reconfiguration of:

• Spectrum Sensing

• Scheduling

• Routing

• Transport

• Etc.

Time

Frequency

Power

Spectrum Hole� White Space

Used Spectrum

c

Spectrum Mobility

Spectrum Sensing

c

Spectrum Mobility involves:•PU Detection•RF Reconfiguration•Spectrum Sharing in new band

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Spectrum Mobility

� Network Protocol Adaptation: e.g.

– Update Routing Information

– Higher layer protocols need to be adapted after spectrum mobility

Network ProtocolAdaption

Channel Condition Changes,

PU detected

spectrumdecision

Spectrummobility

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Spectrum Mobility and TCP

� Route disruptions due to Spectrum Sensing – Different to MANETs node mobility as route is only temporary not available

– Need to take into account limited buffer and temporary off conditions due to sensing

� Large Bandwidth variations– Available spectrum may change frequently � frequent change in available

BW

– Congestion control in TCP relies on incoming ACKs

– TCP cannot effectively adjust to sudden changes in available BW

– New approaches for bandwidth estimation required

� Throughput versus sensing tradeoff– Large sensing time� good PU activity estimation � low throughput

– Small sensing time � wrongly estimated PU activity might lead to collisions

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Transport Layer Issues

� CRAHNs impose unique challenges– impact of sensing time, PU activity and channel heterogeneity?

• For given PU activity, there is optimal selection of <sensing, transmitting> = < ts; To > parameters which maximizes the TCP performance

• sensing interval: trade-off between (i) accurate PU detection and (ii) channel utilization

• ts < 0.2s, � CR user might misdetect the presence of the PU on the current channel �PU collisions lead to TCP packet loss. ts > 0.2s � total delay may trigger RTO

• Vegas may underestimate available BW due to sensing

[Felice10] α=β=0.5To=0.6

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� CRAHNs impose unique challenges– impact of sensing time, PU activity and channel heterogeneity

• Short ON/OFF � a PU might arrive during transmitting period of CR users, even if the channel was found free during sensing.

• A long OFF-period allows the CR users to increase the CW significantly which leads to increase in throughput.

• Spectrum handoff may cause RTO timeout

Long ON/long OFF

Short ON/Short OFF Long ON/short OFF

short ON/long OFF

[Felice10]

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� CRAHNs impose unique challenges– macroscopic level e.g. measuring the aggregate throughput vs. microscopic level

(RTT and CW dynamics) for To=0.6s, no PU

– Sensing leads to RTO timeouts

[Felice10]

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� CRAHNs impose unique challenges– Adaptation to PU activity: Due to AIMD, cannot rapidly adapt to changes in channel

bandwidth availability (single hop case)

[Felice10]

New TCP variants that cope with sensing and

variable PU activity and channel heterogeneity

need to be developed

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Overview


– Introduction




– Introduction





� Conclusion

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Conclusion

� Future wireless networks need better spectrum coordination to increase capacity

� Multi-Radio Multi-Channel Mesh Networks as an example of current systems working on static allocation

� Shortages of spectrum will occur under static allocation � Dynamic Spectrum Access

� Promising cognitive radio based approaches:– Spectrum agile radio with interference avoidance

– Cognitive Basestation and terminals

– Adaptive networks via ad-hoc collaboration

� Early prototypes available for some of these approaches. Different complexity factors and business model implications

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Conclusion

� Cognitive radio networks require large amount of network (and channel) state information to enable efficient – Discovery

– Self-organization

– Cooperation Techniques

� Tradeoff between amount of information exchanged versus decisionmaking capabilities

� Need techniques that facilitate optimising/reasoning under uncertain information

� In addition: – Advances in cognitive radio technology

– New Network Architectures and Information Models that support these

• E.g. Spectrum Coordination Mechanisms, Spectrum Servers for sharing of spectrum information (e.g. Microsoft Initiative)

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Research Challenges

� Architecture and design of adaptive wireless networks based on CRs

� Cooperative spectrum sensing for link and network layers

� Medium Access Control

� Cross-layer radio resource optimization– Mobility management ?

– Resource allocation (time, sub-carrier, code,..)

– Connection management

� Network layer issues such as routing, decision on switching, self-organized networking, …

� Trusted access and security

� Evaluation of large-scale cognitive radio (ad-hoc) systems

� Spectrum measurement campaigns and field validation

� Cognitive radio hardware and software platforms

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Literature

� [Akyildiz09]: Akyildiz, I.F., Lee W. Y., and Chowdhury, K., "CRAHNs: Cognitive Radio Ad Hoc Networks," Ad Hoc Networks (Elsevier) Journal, Vol. 7, No. 5, pp. 810-836, July 2009.

� [Bernardo09] F. Bernardo, R. Augusti, J. Perez-Romero and O. Sallent: ”Distributed Spectrum Management based on Reinforcement Learning”. In Proc. of CROWNCOM'09, Hannover, 2009.

� [Chetret04] D. Chetret, C. Tham and L. Wong. Reinforcement Learning and CMAC-based Adaptive Routing for MANETs. in Proc. of ICON'04, pp. 540-544, 2004.

� [Clancy07] C. Clancy, J. Hecker, E. Stuntebeck and T. O'Shea Applications of Machine Learning to Cognitive Radio Networks. In Wireless Communications, 14(4):47-52, 2007.

� [Ding09]: Lei Ding, Tommaso Melodia, Stella Batalama, Michael Medley, “ROSA: Distributed Joint Routing and Dynamic Spectrum Allocation in Cognitive Radio Ad Hoc Networks,” in Proc. of ACM Intl. Conf. on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), Tenerife, Canary Islands, Spain, Oct. 2009

� [Dowling05] J. Dowling, E. Curran, R. Cunningham and V. Cahill, Using Feedback in Collaborative Reinforcement Learning to Adaptively Optimize MANET Routing. In IEEE Transactions on Systems, Man and Cybernetics, 35(3):360-372, 2005

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Literature

� [Felice10]: Marco Di Felice, Kaushik Roy Chowdhury, Luciano Bononi, Andreas Kassler, Wooseong Kim: End-to-end Protocols for Cognitive Radio Ad Hoc Networks: An Evaluation Study. To appear in: Elsevier Performance Evaluation Journal, Special Issue

� [Foster07] A. Forster. Machine Learning Techniques Applied for Wireless Ad-Hoc Networks: Guide and Survey. In Proc. of ISSNIP'07 , pp. 367-370, Melbourne, 2007.

� [Kim2010]: Wooseong Kim, Andreas J. Kassler, Marco Di Felice and Mario Gerla, ”Cognitive Multi-Radio Mesh Networks for the Future Wireless Internet”, in: Proceedings of 5. Fachgespräch der GI/ITG-Fachgruppe KuVS zum „Future Internet“, 9. Juni 2010, Stuttgart, Germany

� [Mitola99] J. Mitola, “Cognitive Radio for Flexible Mobile Multimedia Communications”, IEEE Mobile Multimedia Conference, 1999, pp3-10

� [Ray08]: Dipankar Raychaudhury: Architecture and Protocol Design for Cognitive Radio Networks, Cognitive Wireless Networking Summit 2008

� [Samptah08]: Ashwin Sampath, Lei Yang, Lili Cao, Haitao Zheng and Ben Y. Zhao: High Throughput Spectrum-aware Routing for Cognitive Radio Networks, in: Proceedings of Third International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), Singapore, May, 2008.

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Literature

� [Yuan07] Yuan Yuan, Paramvir Bahl, Ranveer Chandra, Thomas Moscibroda, Yunnan Wu: Allocating Dynamic Time-Spectrum Blocks In Cognitive Radio Networks, MobiHoc’07, September 9–14, 2007, Montreal, Canada

� [YuanY07] Yuan Yuan Bahl, P. Chandra, R. Chou, P.A. Ferrell, J.I. Moscibroda, T. Narlanka, S. Yunnan Wu, 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2007. DySPAN 2007.

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Multi-Radio Mesh Networks

Literature

� [Banerjee-SIGMETRICS-2006] Arunesh Mishra, Vivek Shrivastava, Suman Banerjee, William A. Arbaugh: Partially overlapped channels not considered harmful. , Proceedings of the joint international conference on Measurement and modeling of computer systems, Saint Malo, France 2006

� [Subramanian08] Anand Prabhu Subramanian, Himanshu Gupta and Samir Das: Minimum Interference Channel Assignment in Multi-Radio Wireless Mesh Networks, IEEE Transactions on Mobile Computing (TMC), Vol 7. Number 11. November 2008.

� [So-MobiHoc-2004] J. So and N. Vaidya. Multi-Channel MAC for Ad Hoc Networks: Handling Multi-Channel Hidden Terminals Using A Single Transceiver. In Proc. ACM MobiHoc, Tokyo, Japan, May 2004.

� [Draves04] R. Draves, J. Padhye and B. Zill, "Comparison of Routing Metrics for Multi-Hop Wireless Networks", Proceedings of ACM SIGCOMM 2004.

� [Adya-04] Atul Adya, Paramvir Bahl, Ranveer Chandra, Lili Qiu: Architecture and techniques for diagnosing faults in IEEE 802.11 infrastructure networks. MOBICOM 2004: 30-44

� [Marina-05]M. Marina, S. Das, A topology control approach for utilizing multiple channels in multi-radio wireless mesh networks, in: 2nd International Conference on Broadband Networks (Broadnets 2005), Boston, Massachusetts – USA, October 2005.

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Literature

� [DAS05]A. Das, H. Alazemi, R. Vijayakumar, S. Roy, Optimization models for fixed channel assignment in wireless mesh networks with multiple radios, in: 2nd IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON), Santa Clara, California – USA, September 2005.

� [Tang05]J. Tang, G. Xue, W. Zhang, Interference-aware topology control and QoSrouting in multi-channel wireless mesh networks, in: 6th ACM International Symposium on Mobile Ad Hoc Networking and Computing (Mobihoc 2005), Urbana-Champaigne, Illinois – USA, 2005.

� [Ramachandran06] K. Ramachandran, E. Belding, K. Almeroth, M.Buddhikot, Interference-aware channel assignment in multi-radio wireless mesh networks, in: 25th Conference on Computer Communications (Infocom 2006), Barcelona – Spain, April 2006.

� [Raniwala04] A. Raniwala, K. Gopalan, T. Chiueh, Centralized channel assignment and routing algorithms for multi-channel wireless mesh networks, Mobile Computing and Communications Review 8 (2) (2004) 50–65.

� [Raniwala05] A. Raniwala, T. Chiueh, Architecture and algorithms for an ieee 802.11-based multi-channel wireless mesh network, in: 24th Conference on Computer Communications (Infocom 2005), Miami, Florida – USA, March 2005.

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Literature

� [Bahl04] P. Bahl, R. Chandra, J. Dunagan. SSCH: Slotted seeded channel hopping for capacity improvement in ieee 802.11 adhoc wireless networks, in: 10th ACM International Conference on Mobile Computing and Networking (MobiCom 2004), Philadelphia, Pennsylvania – USA, 2004

� [Jain01]N. Jain, S. Das, A. Nasipuri, A multichannel csma mac protocol with receiver-based channel selection for multihop wireless networks, in: 10th International Conference on Computer Communications and Networks (ICCCN 2001), Scottsdale, Arizona – USA, 2001.

� [Kyasanur06] P. Kyasanur, N. Vaidya, Routing and link-layer protocols for multi-channel multi-interface ad hoc wireless networks, SIGMOBILE Mobile Computing and Communications Review 10 (1) (2006) 31–43.

� [Kas10a] Marcel Castro, Andreas J. Kassler: Measuring the Impact of ACI in Cognitive Multi-Radio Mesh Networks, In: IEEE 72nd Vehicular Technology Conference (VTC Fall 2010), 6–9 September 2010, Ottawa, Canada

� [Kas10b] Peter Dely, Marcel Castro, Sina Soukhakian, Arild Moldsvar, Andreas Kassler: Practical Considerations for Channel Assignment in Wireless Mesh Networks, In IEEE Globecom 2010 Workshop on Broadband Wireless Access (BWA 2010), December 6th 2010, Miami, USA

� [Lav10] Andreas Lavén and Andreas Kassler, Multi-Channel Anypath Routing in Wireless Mesh Networks, In: IEEE Globecom 2010 Workshop on Heterogeneous, Multi-hop Wireless and Mobile Networks (HeterWMN 2010), December 2010, Miami, USA.

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Thank you!Andreas J. Kassler - [email protected]

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Cognitive Radio Multihop/- Mesh Networks

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