1 Networking Cognitive Radios Interaction Problem Role of Policy Techniques for designing network Commercial standards

1

Networking Cognitive Radios

• Interaction Problem• Role of Policy• Techniques for

designing network• Commercial standards

Cognitive Radio Technologies, 2007

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The Interaction Problem

• Outside world is determined by the interaction of numerous cognitive radios

• Adaptations spawn adaptations

OutsideWorld


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Dynamic Spectrum Access Pitfall• Suppose

– g31>g21; g12>g32 ;

g23>g13

• Without loss of generality– g31, g12, g23 = 1– g21, g32, g13 = 0.5

• Infinite Loop!– 4,5,1,3,2,6,4,…

Chan. (0,0,0) (0,0,1) (0,1,0) (0,1,1) (1,0,0) (1,0,1) (1,1,0) (1,1,1)

Interf. (1.5,1.5,1.5) (0.5,1,0) (1,0,0.5) (0,0.5,1) (0,0.5,1) (1,0,0.5) (0.5,1,0) (1.5,1.5,1.5)

Interference Characterization

0 1 2 3 4 5 6 7

1

2

3


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Implications• In one out every four deployments, the

example system will enter into an infinite loop• As network scales, probability of entering an

infinite loop goes to 1:– 2 channels– k channels

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

31 3/ 4 n Cp loop

111 1 2n kCkp loop


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Locally optimal decisions that lead to globally undesirable networks

• Scenario: Distributed SINR maximizing power control in a single cluster

• For each link, it is desirable to increase transmit power in response to increased interference

• Steady state of network is all nodes transmitting at maximum power

Power

SINR

Insufficient to consider only a single link, must consider interaction


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1. Steady state characterization

2. Steady state performance

3. Convergence4. Stability/Noise5. Scalability

a1

a2

NE1

NE2

NE3

a1

a2

NE1

NE2

NE3

a1

a2

NE1

NE2

NE3

a1

a2

NE1

NE2

NE3

a3

Steady State Characterization Is it possible to predict behavior in the system? How many different outcomes are possible?

Performance Are these outcomes desirable? Do these outcomes maximize the system target parameters?

Convergence How do initial conditions impact the system steady state? What processes will lead to steady state conditions? How long does it take to reach the steady state?

Stability/Noise How do system variations/noise impact the system? Do the steady states change with small variations/noise? Is convergence affected by system variations/noise?

Scalability As the number of devices increases, How is the system impacted? Do previously optimal steady states remain optimal?

Network Analysis Objectives

(Radio 1’s available actions)

(Rad

io 2

’s a

vaila

ble

actio

ns)


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Cognitive Radio Network Modeling Summary

• Radios• Actions for each radio• Observed Outcome

Space• Goals• Decision Rules• Timing

• i,j N, |N| = n

• A=A1A2An

• O

• uj:O (uj:A)

• dj:OAi (dj:A Ai)

• T=T1T2Tn


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Comments on Timing• When decisions are

made also matters and different radios will likely make decisions at different time

• Tj – when radio j makes its adaptations– Generally assumed to be

an infinite set– Assumed to occur at

discrete time• Consistent with DSP

implementation

• T=T1T2Tn

• t T

Decision timing classes• Synchronous

– All at once

• Round-robin– One at a time in order– Used in a lot of analysis

• Random– One at a time in no order

• Asynchronous– Random subset at a time– Least overhead for a

network


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Variety of game models• Normal Form Game <N,A,{ui}>

– Synchronous play– T is a singleton– Perfect knowledge of action space, other players’ goals (called

utility functions)• Repeated Game <N,A,{ui},{di}>

– Repeated synchronous play of a normal form game– T may be finite or infinite– Perfect knowledge of action space, other players’ goals (called

utility functions)– Players may consider actions in future stages and current stages

• Strategies (modified di)

• Asynchronous myopic repeated game <N,A,{ui},{di},T>– Repeated play of a normal form game under various timings– Radios react to most recent stage, decision rule is “intelligent”

• Many others in the literature and in the dissertation


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NormalUrgent

Allocate ResourcesInitiate Processes

OrientInfer from Context

Establish Priority

PlanNormal

Negotiate

Immediate

LearnNewStates

Goal

Adapted From Mitola, “Cognitive Radio for Flexible Mobile Multimedia Communications ”, IEEE Mobile Multimedia Conference, 1999, pp 3-10.

Observe

OutsideWorld

Decide

Act

Autonomous

Infer from Radio Model

States

\

Utility functionArguments

Utility Function

Outcome Space

Action Sets

DecisionRules

Cognitive radios are naturally modeled as players in a game


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Radio 2

Actions

Radio 1

ActionsAction Space

u2u1

Decision Rules

Decision Rules

Outcome Space

:f A OInformed by Communications Theory

1 2ˆ ˆ, 1 1̂u 2 2ˆu

Interaction is naturally modeled as a game


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Some differences between game models and cognitive radio network model

Player Cognitive Radio

Knowledge Knows A Can learn O (may know or learn A)

f : A O

Invertible

Constant

Known

Not invertible (noise)

May change over time (though relatively fixed for short periods)

Has to learn

Preferences Ordinal Cardinal (goals)

• Assuming numerous iterations, normal form game only has a single stage.– Useful for compactly capturing modeling components at a single stage– Normal form game properties will be exploited in the analysis of other

games• Repeated games are explicitly used as the basis for cognitive radio

algorithm design (e.g., Srivastava, MacKenzie)– Not however, focus of work– Not the most commonly encountered implementation


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Cognitive Radios’ Dilemma• Two radios have two

signals to choose between {n,w} and {N,W}

• n and N do not overlap

• Higher throughput from operating as a high power wideband signal when other is narrowband


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Potential Problems with Networked Cognitive Radios

Distributed• Infinite recursions• Instability (chaos)• Vicious cycles• Adaptation collisions• Equitable distribution of

resources• Byzantine failure• Information distribution

Centralized• Signaling Overhead• Complexity• Responsiveness• Single point of failure


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Price of Anarchy (Factor)

• Centralized solution always at least as good as distributed solution– Like ASIC is always at least as good as

DSP

• Ignores costs of implementing algorithms– Sometimes centralized is infeasible (e.g.,

routing the Internet)– Distributed can sometimes (but not

generally) be more costly than centralized

Performance of Centralized Algorithm Solution

Performance of Distributed Algorithm Solution

1

9.6

7


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Implications• Best of All Possible Worlds

– Low complexity distributed algorithms with low anarchy factors• Reality implies mix of methods

– Hodgepodge of mixed solutions• Policy – bounds the price of anarchy• Utility adjustments – align distributed solution with centralized

solution• Market methods – sometimes distributed, sometimes centralized• Punishment – sometimes centralized, sometimes distributed,

sometimes both• Radio environment maps –”centralized” information for distributed

decision processes– Fully distributed

• Potential game design – really, the panglossian solution, but only applies to particular problems

17

The Role of Policy

How does policy impact network performance?


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Policy• Concept: Constrain the

available actions so the worst cases of distributed decision making can be avoided

• Not a new concept – – Policy has been used since

there’s been an FCC

• What’s new is assuming decision makers are the radios instead of the people controlling the radios


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Policy applied to radios instead of humans

• Need a language to convey policy– Learn what it is– Expand upon policy later

• How do radios interpret policy– Policy engine?

• Need an enforcement mechanism– Might need to tie in to humans

• Need a source for policy– Who sets it?– Who resolves disputes?

• Logical extreme can be quite complex, but logical extreme may not be necessary.

Policiesfrequency

mask


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Example Policies from WNAN• No harmful interference to non-WNaN systems

– Perhaps not practical (then again, only a “principle”)• Interference Limitation: Maintain ≤ 3dB of SNR

at a Protected Receiver.– More practical, though perhaps not measurable – Possible to estimate with built in environment

models• Abandon Time: Abandon a Frequency ≤ 500

ms– Easily measured– Depending on precise policy, easily implemented

too– Probably should be augmented with detection


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• Detection– Digital TV: -116 dBm over a 6 MHz channel– Analog TV: -94 dBm at the peak of the NTSC

(National Television System Committee) picture carrier

– Wireless microphone: -107 dBm in a 200 kHz bandwidth.

• Transmitted Signal– 4 W Effective Isotropic Radiated Power (EIRP)– Specific spectral masks – Channel vacation times

C. Cordeiro, L. Challapali, D. Birru, S. Shankar, “IEEE 802.22: The First Worldwide Wireless Standard based on Cognitive Radios,” IEEE DySPAN2005, Nov 8-11, 2005 Baltimore, MD.

802.22 Example Policies

22

Designing Well-Behaved Cognitive Radio NetworksRepeated Games, Potential Games, Markets


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Repeated GamesStage 1

Stage 2

Stage k

Stage 1

Stage 2

Stage k

• Same game is repeated– Indefinitely– Finitely

• Players consider discounted payoffs across multiple stages– Stage k

– Expected value over all future stages

k k ki iu a u a

0

k k ki i

k

u a u a


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Impact of Strategies• Rather than merely reacting to the state of the network,

radios can choose their actions to influence the actions of other radios

• Threaten to act in a way that minimizes another radio’s performance unless it implements the desired actions

• Common strategies– Tit-for-tat– Grim trigger– Generous tit-for-tat

• Play can be forced to any “feasible” payoff vector with proper selection of punishment strategy.


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Impact of Communication on Strategies

nada

c

Nada C

0,0 -5,5

-1,15,-5

N

-100,0

-100,-1

n -1,-1000,-100 -100,-100

• Players agree to play in a certain manner• Threats can force play to almost any state

– Breaks down for finite number of stages


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Improvement from Punishment

A. MacKenzie and S. Wicker, “Game Theory in Communications: Motivation, Explanation, and Application to Power Control,” Globecom2001, pp. 821-825.

• Throughput/unit power gains be enforcing a common received power level at a base station

• Punishment by jamming

• Without benefit to deviating, players can operate at lower power level and achieve same throughput


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Instability in Punishment• Issues arise when

radios aren’t directly observing actions and are punishing with their actions without announcing punishment

• Eventually, a deviation will be falsely detected, punished and without signaling, this leads to a cascade of problems

V. Srivastava, L. DaSilva, “Equilibria for Node Participation in Ad Hoc Networks – An Imperfect Monitoring Approach,” ICC 06, June 2006, vol 8, pp. 3850-3855


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Comments on Punishment• Works best with a common controller to announce• Problems in fully distributed system

– Need to elect a controller– Otherwise competing punishments, without knowing other

players’ utilities can spiral out of control

• Problems when actions cannot be directly observed– Leads to Byzantine problem

• No single best strategy exists– Strategy flexibility is important – Significant problems with jammers (they nominally receive

higher utility when “punished”

• Generally better to implement centralized controller– Operating point has to be announced anyways


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Cost Adjustments• Concept: Centralized unit dynamically adjusts

costs in radios’ objective functions to ensure radios operate on desired point

• Example: Add -12 to use of wideband waveform

i i iu a u a c a


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Comments on Cost Adjustments• Permits more flexibility than policy

– If a radio really needs to deviate, then it can

• Easy to turn off and on as a policy tool– Example: protected user shows up in a

channel, cost to use that channel goes up– Example: prioritized user requests channel,

other users’ cost to use prioritized user’s channel goes up (down if when done)


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Global Altruism: distributed, but more costly• Concept: All radios distributed all relevant information

to all other radios and then each independently computes jointly optimal solution– Proposed for spreading code allocation in Popescu04, Sung03

• C = cost of computation• I = cost of information transfer from node to node• n = number of nodes• Distributed

– nC + n(n-1)I/2• Centralized (election)

– C + 2(n-1)I• Price of anarchy = 1• May differ if I is asymmetric


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Improving Global Altruism• Global altruism is clearly inferior to a centralized solution

for a single problem. • However, suppose radios reported information to and

used information from a common database– n(n-1)I/2 => 2nI

• And suppose different radios are concerned with different problems with costs C1,…,Cn

• Centralized– Resources = 2(n-1)I + sum(C1,…,Cn)– Time = 2(n-1)I + sum(C1,…,Cn)

• Distributed– Resources = 2nI + sum(C1,…,Cn)– Time = 2I + max (C1,…,Cn)


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Example Application: • Overlay network of secondary

users (SU) free to adapt power, transmit time, and channel

• Without REM:– Decisions solely based on link

SINR• With REM

– Radios effectively know everythingUpshot: A little gain for the secondary users; big gain for primary users

From: Y. Zhao, J. Gaeddert, K. Bae, J. Reed, “Radio Environment Map Enabled Situation-Aware Cognitive Radio Learning Algorithms,” SDR Forum Technical Conference 2006.


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Comments on Radio Environment Map

• Local altruism also possible– Less information transfer

• Like policy, effectively needs a common language

• Nominally could be centralized or distributed database


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Potential Games• Existence of a function (called

the potential function, V), that reflects the change in utility seen by a unilaterally deviating player.

• Cognitive radio interpretation:– Every time a cognitive radio

unilaterally adapts in a way that furthers its own goal, some real-valued function increases.

time

(

)


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Exact Potential Game Forms• Many exact potential games can be recognized

by the form of the utility function


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Implications of Monotonicity• Monotonicity implies

– Existence of steady-states (maximizers of V)– Convergence to maximizers of V for numerous combinations

of decision timings decision rules – all self-interested adaptations

• Does not mean that that we get good performance– Only if V is a function we want to maximize


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Interference Reducing Networks

• Concept– Cognitive radio network is a potential game with a potential

function that is negation of observed network interference• Definition

– A network of cognitive radios where each adaptation decreases the sum of each radio’s observed interference is an IRN

• Implementation:– Design DFS algorithms such that network is a potential game

with -V

ii N

I

time

(

)


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Bilateral Symmetric Interference

• Two cognitive radios, j,kN, exhibit bilateral symmetric interference if

Source: http://radio.weblogs.com/0120124/Graphics/geese2.jpg

What’s good for the goose, isgood for the gander…

, ,jk j j k kj k k jg p g p ,j j k k k – waveform of radio k• pk - the transmission power of

radio k’s waveform• gkj - link gain from the

transmission source of radio k’s signal to the point where radio j measures its interference,

• - the fraction of radio k’s signal that radio j cannot exclude via processing (perhaps via filtering, despreading, or MUD techniques).

,k j


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Bilateral Symmetric Interference Implies an Interference Reducing Network

• Cognitive Radio Goal:• By bilateral symmetric interference

• Rewrite goal

• Therefore a BSI game (Si =0)

• Interference Function

• Therefore profitable unilateral deviations increase V and decrease () – an IRN

iNj

jijjiii pgIu\

,

\

,i ik i kk N i

u b

1

1

,i

ki k k ii N k

V g p

2V

kiikikkikiiikikkki bbpgpg ,,,,


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An IRN 802.11 DFS Algorithm• Suppose each access node

measures the received signal power and frequency of the RTS/CTS (or BSSID) messages sent by observable access nodes in the network.

• Assumed out-of-channel interference is negligible and RTS/CTS transmitted at same power

jkkkjkjjjk ffpgffpg ,,

\

,i i ki k i kk N i

u f I f g p f f

1

,0

i ki k

i k

f ff f

f f

Listen onChannel LC

RTS/CTSenergy detected? Measure power

of access node in message, p

Note address of access node, a

Update interference

tableTime for decision?

Apply decision criteria for new

operating channel, OCUse 802.11h

to signal change in OC to clients

yn

Pick channel tolisten on, LC

y

n

Start


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Statistics• 30 cognitive access nodes in European UNII

bands• Choose channel with lowest interference• Random timing• n=3• Random initial channels• Randomly distributed positions over 1 km2

0 10 20 30 40 50 60 70 80 90 1000

10

20

30

40

50

60

70

Number of Access Nodes

Red

uctio

n in

Net

Int

erfe

renc

e (d

B)

Round-robin Asynchronous Legacy Devices

Reduction in Net Interference

Reduction in Net Interference


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Ad-hoc Network

• Possible to adjust previous algorithm to not favor access nodes over clients

• Suitable for ad-hoc networks


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Comments on Potential Games• All networks for which there is not a better response interaction loop

is a potential game• Before implementing fully distributed GA, SA, or most CBR decision

rules, important to show that goals and action satisfy potential game model

• Sum of exact potential games is itself an exact potential game– Permits (with a little work) scaling up of algorithms that adjust single

parameters to multiple parameters • Possible to combine with other techniques

– Policy restricts action space, but subset of action space remains a potential game (see J. Neel, J. Reed, “Performance of Distributed Dynamic Frequency Selection Schemes for Interference Reducing Networks,” Milcom 2006)

– As a self-interested additive cost function is also a potential game, easy to combine with additive cost approaches (see J. Neel, J. Reed, R. Gilles, “The Role of Game Theory in the Analysis of Software Radio Networks,” SDR Forum02)

• More on potential games:– Chapter 5 in Dissertation of J. Neel, Available at

http://scholar.lib.vt.edu/theses/available/etd-12082006-141855/


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Token Economies• Pairs of cognitive radios exchange tokens for

services rendered or bandwidth rented• Example:

– Primary users leasing spectrum to secondary users • D. Grandblaise, K. Moessner, G. Vivier and R. Tafazolli,

“Credit Token based Rental Protocol for Dynamic Channel Allocation,” CrownCom06.

– Node participation in peer-to-peer networks• T. Moreton, “Trading in Trust, Tokens, and Stamps,”

Workshop on the Economics of Peer-to-Peer Systems, Berkeley, CA June 2003.

• Why it works – it’s a potential game when there’s no externality to the trade


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Comments on Network Options• Approaches can be combined

– Policy + potential– Punishment + cost adjustment– Cost adjustment + token economies

• Mix of centralized and distributed• Potential game approach has lowest complexity,

but cannot be extended to every problem• Token economies requires strong property rights

to ensure • Punishment can also be implemented at a choke

point in the network

47

Commercial Cognitive Radio Standards802.11h,y, 802.16h, 802.22


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• Explicitly opened up Japanese spectrum for 5 GHz operation

• Part of larger effort to force equipment to operate based on geographic region, i.e., the local policy

Lower Upper

U.S. 2.402 2.48Europe 2.402 2.48Japan 2.473 2.495Spain 2.447 2.473France 2.448 2.482

2.4 GHz

USUNII Low 5.15 – 5.25 (4) 50 mWUNII Middle 5.25 – 5.35 (4) 250 mWUNII Upper 5.725-5.825 (4) 1 W5.47 – 5.725 GHz released in Nov 2003

Europe5.15-5.35 200 mW5.47-5.725 1 W

Japan4.9-5.0915.15-5.25 (10 mW/MHz) unlicensed

5 GHz

802.11j – Policy Based Radio


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• Enhances QoS for Voice over Wireless IP (aka Voice over WiFi ) and streaming multimedia

• Changes– Enhanced Distributed Coordination Function (EDCF)

• Shorter random backoffs for higher priority traffic

– Hybrid coordination function (orientation)• Defines traffic classes

• In contention free periods, access point controls medium access (observation)

• Stations report to access info on queue size. (Distributed sensing)

802.11e – Almost Cognitive


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• Dynamic Frequency Selection (DFS)– Avoid radars

• Listens and discontinues use of a channel if a radar is present

– Uniform channel utilization

• Transmit Power Control (TPC)– Interference reduction– Range control– Power consumption Savings– Bounded by local regulatory

conditions

802.11h – Unintentionally Cognitive


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802.11h: A simple cognitive radio

Observe– Must estimate channel characteristics (TPC)– Must measure spectrum (DFS)

Orientationa) Radar present? b) In band with satellite??c) Bad channel?d) Other WLANs?

Decision – Change frequency– Change power– Nothing

Action Implement decision

Learn– Not in standard, but most implementations should learn the environment to

address intermittent signals

Outside World

Observe

OrientDecide

Act

Learn


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• Wireless Regional Area Networks (WRAN)– Aimed at bringing broadband access in rural and

remote areas– Takes advantage of better propagation characteristics

at VHF and low-UHF– Takes advantage of unused TV channels that exist in

these sparsely populated areas

• 802.22 is to define:– Physical layer specifications– Policies and procedures for operation in the VHF/UHF

TV Bands between 54 MHz and 862 MHz– Cognitive Wireless RAN Medium Access Control

IEEE 802.22


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802.22 Status and ObjectivesObjectives

• Specify PHY and MAC for fixed point-to-multipoint wireless regional area networks operating in the VHF/UHF TV broadcast bands between 54 MHz and 862 MHz.

• Strict non-interference with incumbent licensed services.

• Aimed at bringing broadband access in rural and remote areas

Status• 10 proposals merged

into 1 draft proposal at March Plenary (March 5-10, Denver CO)

• Still working on bringing to ballot

PAR: http://www.ieee802.org/22/802-22_PAR.pdf

http://www.ieee802.org/22/802-22_PAR.pdf


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802.22 Deployment Scenario• Devices

– Base Station (BS)– Customer Premise Equipment

(CPE)• Master/Slave relation

– BS is master– CPE slave

• Max Transmit CPE 4W

Figure from: IEEE 802.22-06/0005r1


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• Data Rates 5 Mbps – 70 Mbps• Point-to-multipoint TDD/FDD• DFS, TPC• Adaptive Modulation

– QPSK, 16, 64-QAM, Spread QPSK

• OFDMA on uplink and downlink• Use multiple contiguous TV channels when available• Fractional channels (adapting around microphones)• Space Time Block Codes• Beam Forming

– No feedback for TDD (assumes channel reciprocity)

• 802.16-like ranging

Proposed PHY Features of 802.22


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Possible MAC Features of 802.22• 802.16 MAC plus the following

– Multiple channel support– Coexistence

• Incumbents• BS synchronization• Dynamic resource sharing

– Clustering support– Signal detection/classification routines

• Security based on 802.16e security


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• Observation– Signal strength and feature detection– Aided by distributed sensing (CPEs return data to BS)– Digital TV: -116 dBm over a 6 MHz channel– Analog TV: -94 dBm at the peak of the NTSC (National Television

System Committee) picture carrier– Wireless microphone: -107 dBm in a 200 kHz bandwidth.– Possibly aided by spectrum usage tables

• Orientation– Infer type of signals that are present

• Decision– Frequencies, modulations, power levels, antenna choice (omni and

directional)• Policies

– 4 W Effective Isotropic Radiated Power (EIRP)– Spectral masks, channel vacation times

C. Cordeiro, L. Challapali, D. Birru, S. Shankar, “IEEE 802.22: The First Worldwide Wireless Standard based on Cognitive Radios,” IEEE DySPAN2005, Nov 8-11, 2005 Baltimore, MD.

Cognitive Aspects of 802.22


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Sensing Aspects of 802.22• Region based sensing

– Remote aided sensing• Algorithm:

– Partition cell into disjoint regions

– For each region assign a remote (Customer Premise Equipment)

• Example considered squares with 500 m sides

– CPE feeds back what it finds

• Number of incumbents• Occupied bands

Source: IEEE 802.22-06/0048r0

0 10 20 30 40 50 60 70 80 90 1000

10

20

30

40

50

60

70

80

90

100

Grid Index X

Grid

Ind

ex Y

CPE Number = 400, IT Number = 4


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802.16h• Draft to ballot Oct 06,

67% approve, resolving comments)

• Improved Coexistence Mechanisms for License-Exempt Operation

• Basically, a cognitive radio standard

• Incorporates many of the hot topics in cognitive radio

– Token based negotiation– Interference avoidance– Network collaboration– RRM databases

• Coexistence with non 802.16h systems

– Regular quiet times for other systems to transmit

From: M. Goldhamer, “Main concepts of IEEE P802.16h / D1,” Document Number: IEEE C802.16h-06/121r1, November 13-16, 2006.


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General Cognitive Radio Policies in 802.16h• Must detect and avoid radar and other higher

priority systems• All BS synchronized to a GPS clock• All BS maintain a radio environment map (not

their name) • BS form an interference community to resolve

interference differences• All BS attempt to find unoccupied channels first

before negotiating for free spectrum– Separation in frequency, then separation in time


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DFS in 802.16h• Adds a generic

algorithm for performing Dynamic Frequency Selection in license exempt bands

• Moves systems onto unoccupied channels based on observations

Generic DFS Operation Figure h1(fuzziness in original)


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Adaptive Channel Selection• Used when BS turns on• First – attempt to find a

vacant channel– Passive scan– Candidate Channel

Determination– Messaging with Neighbors

• Second – attempt to coordinate for an exclusive channel

• If unable to find an empty channel, then BS attempts to join the interference community on the channel it detected the least interference

Figure h37: IEEE 802.16h-06/010 Draft IEEE Standard for Local and metropolitan area networks Part 16: Air Interface for Fixed Broadband Wireless Access Systems Amendment for Improved Coexistence Mechanisms for License-Exempt Operation, 2006-03-29


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Collaboration• BS can request interfering

systems to back off transmit power

• Master BS can assign transmit timings– Intended to support up to 3

systems (Goldhammer)

• Slave BS in an interference community can “bid” for interference free times via tokens.

• Master BS can advertise spectrum for “rent” to other Master BS– Bid by tokens

• Collaboration supported via Base Station Identification Servers, messages, and RRM databases

• Interferer identification by finding power, angle of arrival, and spectral density of OFDM/OFDMA preambles

• Every BS maintains a database or RRM information which can be queried by other BS– This can also be hosted

remotely


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802.16h• Improved Coexistence

Mechanisms for License-Exempt Operation

• Explicitly, a cognitive radio standard

• Incorporates many of the hot topics in cognitive radio

– Token based negotiation

– Interference avoidance

– Network collaboration– RRM databases

• Coexistence with non 802.16h systems

– Regular quiet times for other systems to transmit

From: M. Goldhamer, “Main concepts of IEEE P802.16h / D1,” Document Number: IEEE C802.16h-06/121r1, November 13-16, 2006.


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• Ports 802.11a to 3.65 GHz – 3.7 GHz (US Only) – FCC opened up band in July 2005– Ready 2008

• Intended to provide rural broadband access• Incumbents

– Band previously reserved for fixed satellite service (FSS) and radar installations – including offshore

– Must protect 3650 MHz (radar)– Not permitted within 80km of inband government radar– Specialized requirements near Mexico/Canada and other incumbent users

• Leverages other amendments– Adds 5,10 MHz channelization

(802.11j)– DFS for signaling for radar

avoidance (802.11h)• Working to improve channel

announcement signaling • Database of existing devices

– Access nodes register at http://wireless.fcc.gov/uls

– Must check for existing devices at same site

Source: IEEE 802.11-06/0YYYr0

802.11y


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802.11s• Modify 802.11 MAC to create

dynamic self-configuring network of access points (AP) called and Extended Service Set (ESS) Mesh

• Status– Standard out in 2008– Numerous mesh products available

now– Involvement from Mitre, NRL

• Features– Automatic topology learning,

dynamic path selection– Single administrator for 802.11i

(authentication)– Support higher layer connections– Allow alternate path selection

metrics– Extend network merely by

introducing access point and configuring SSID

IP or Ethernet


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Networking Summary• Many different solutions

– Inferring context to select appropriate solution is important

• Centralized solutions always present the option of the optimal solution, but may not find the solution in a useful amount of time or may be overly complex

• Distributed solutions (generally) find solutions faster and with less complexity but may be suboptimal

• Techniques for designing cognitive networks rapidly migrating into commercial standards– REMs – 802.11y, 802.16h– Token economy – 802.22– Policy – 802.16h, 802.11, 802.22

Documents

1 Networking Cognitive Radios Interaction Problem Role of Policy Techniques for designing network Commercial standards