Networking Cognitive
Radios
• Interaction Problem
• Role of Policy
• Techniques for
designing network
• Commercial standards
1
The Interaction Problem
Outside
World
• Outside world is determined by the interaction
of numerous cognitive radios
2/67
• Adaptations spawn adaptations
 Cognitive Radio Technologies, 2007
Dynamic Spectrum Access Pitfall
• Suppose
– g31>g21; g12>g32 ;
g23>g13
2
• Without loss of
generality
– g31, g12, g23 = 1
– g21, g32, g13 = 0.5
• Infinite Loop!
3
1
– 4,5,1,3,2,6,4,…
Interference Characterization
Chan.
Interf.
(0,0,0)
(0,0,1)
(0,1,0)
(0,1,1)
(1,0,0)
(1,0,1)
(1,1,0)
(1,1,1)
(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)
3/67
0
1
2
 Cognitive Radio Technologies, 2007
3
4
5
6
7
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:
C
– 2 channels p  loop   1   3 / 4 
– k channels p  loop   1  1  2  k 1  C
• Even for apparently simple algorithms,
ensuring convergence and stability will be
nontrivial
n
3
n
k 1
4/67
 Cognitive Radio Technologies, 2007
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
5/67
interaction
 Cognitive Radio Technologies, 2007
(Radio 2’s available actions)
Network Analysis Objectives
1. Steady state
characterization
2. Steady state performance
3. Convergence
4. Stability/Noise
5. Scalability
NE3
NE3
a2
NE2
NE1
NE1
a1
a1
(Radio 1’s available actions)
a3
Scalability
Convergence
Stability/Noise
Performance
Steady State Characterization
As
Are
How
these
donumber
initial
system
outcomes
of
variations/noise
devices
desirable?
impact
increases,
the
impact
system
the system?
steady state?
Is itthe
possible
toconditions
predict
behavior
in
the
system?
What
Do
these
How
processes
steady
is
outcomes
thestates
system
will outcomes
maximize
lead
change
impacted?
to steady
with
the
system
statevariations/noise?
conditions?
target parameters?
Howthe
many
different
are small
possible?
How
Is
convergence
Do
long
previously
does itaffected
take
optimal
to by
reach
steady
system
thestates
steady
variations/noise?
remain
state?optimal?6/67
 Cognitive Radio Technologies, 2007
Cognitive Radio Network
Modeling Summary
• Radios
• Actions for each radio
• Observed Outcome
Space
• Goals
• Decision Rules
• Timing
• i,j N, |N| = n
• A=A1A2An
• O
• uj:O (uj:A)
• dj:OAi (dj:A Ai)
• T=T1T2Tn
7/67
 Cognitive Radio Technologies, 2007
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=T1T2Tn
• 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
8/67
 Cognitive Radio Technologies, 2007
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
9/67
 Cognitive Radio Technologies, 2007
Cognitive radios are naturally
modeled as players in a game
Infer from Context
Utility function
Arguments
Infer from Radio Model
Establish Priority
Normal
Immediate
Observe
Outcome Space
Outside
World
Utility Function
Orient
Autonomous
Goal
Plan
Normal
Urgent
Learn
New
States
Decide
States
Act
\
Decision
Rules
Allocate Resources
Initiate Processes
Action
Negotiate
 Cognitive Radio Technologies, 2007
Sets
10/67
Adapted From Mitola, “Cognitive Radio for Flexible Mobile Multimedia Communications ”, IEEE Mobile Multimedia Conference, 1999, pp 3-10.
Interaction is naturally modeled
as a game
Radio 1
Radio 2
Actions
Decision
Rules
u1
Actions
Decision
Rules
Action Space
Informed by
Communications
Theory
u 1  ˆ1 
f :AO
Outcome Space
 ˆ1 , ˆ 2 
u 2  ˆ 2 
u2
11/67
 Cognitive Radio Technologies, 2007
Some differences between game models
and cognitive radio network model
• 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
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)
 Cognitive Radio Technologies, 2007
12/67
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
13/67
 Cognitive Radio Technologies, 2007
Potential Problems with
Networked Cognitive Radios
Distributed
•
•
•
•
•
Centralized
Infinite recursions
Instability (chaos)
Vicious cycles
Adaptation collisions
Equitable distribution of
resources
• Byzantine failure
• Information distribution
•
•
•
•
Signaling Overhead
Complexity
Responsiveness
Single point of failure
14/67
 Cognitive Radio Technologies, 2007
Price of Anarchy (Factor)
Performance of Centralized Algorithm Solution
Performance of Distributed Algorithm Solution
1
• 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
 Cognitive Radio Technologies, 2007
9.6
7
15/67
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
16/67
 Cognitive Radio Technologies, 2007
The Role of Policy
How does policy
impact network
performance?
17
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
18/67
 Cognitive Radio Technologies, 2007
Policy applied to radios instead
of humans
mask
• Need a language to convey
policy
– Learn what it is
– Expand upon policy later
frequency
Policies
• 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.
 Cognitive Radio Technologies, 2007
19/67
Example Policies from WNAN
•
No harmful interference to non-WNaN systems
–
•
Interference Limitation: Maintain ≤ 3dB of SNR
at a Protected Receiver.
–
–
•
Perhaps not practical (then again, only a “principle”)
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
20/67
 Cognitive Radio Technologies, 2007
802.22 Example Policies
• 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
21/67
C. Cordeiro, L. Challapali, D. Birru, S. Shankar, “IEEE 802.22: The First Worldwide Wireless Standard based on Cognitive Radios,”

Cognitive
Radio
Technologies,
2007
IEEE DySPAN2005, Nov 8-11, 2005 Baltimore, MD.
Designing Well-Behaved
Cognitive Radio Networks
Repeated
Games,
Potential
Games, Markets
22
Repeated Games
• Same game is repeated
S ta g e 1
– Indefinitely
– Finitely
• Players consider
discounted payoffs
across multiple stages
– Stage k
ui  a
k

  ui  a
k
k

– Expected value over all
future stages

ui
 a    
k
k 0
k
S ta g e 2
ui  a
k

S ta g e k
 Cognitive Radio Technologies, 2007
23/67
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.
24/67
 Cognitive Radio Technologies, 2007
Impact of Communication on
Strategies
• Players agree to play in a certain manner
• Threats can force play to almost any state
– Breaks down for finite number of stages
Nada
C
N
nada
0,0
-5,5
-100,0
c
5,-5
-1,1
-100,-1
n
0,-100
-1,-100 -100,-100
 Cognitive Radio Technologies, 2007
25/67
Improvement from
Punishment
• 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
A. MacKenzie and S. Wicker, “Game Theory in Communications:26/67
Motivation, Explanation, and Application to Power Control,” Globecom2001,
 Cognitive Radio Technologies, 2007
pp. 821-825.
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
27/67
 Cognitive Radio Technologies, 2007
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
28/67
 Cognitive Radio Technologies, 2007
Cost Adjustments
• Concept: Centralized unit dynamically adjusts
costs in radios’ objective functions to ensure
radios operate on desired point
u i  a   u i  a   ci  a 
• Example: Add -12 to use of wideband waveform
29/67
 Cognitive Radio Technologies, 2007
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)
30/67
 Cognitive Radio Technologies, 2007
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
31/67
 Cognitive Radio Technologies, 2007
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)
32/67
 Cognitive Radio Technologies, 2007
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 everything
Upshot: A little gain for the secondary users;
big gain for primary users
33/67
From: Y.
Zhao,
J. Gaeddert,
 Cognitive
Radio
Technologies,
2007
K. Bae, J. Reed, “Radio Environment Map Enabled SituationAware Cognitive Radio Learning Algorithms,” SDR Forum Technical Conference 2006.
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
34/67
 Cognitive Radio Technologies, 2007
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 realvalued function increases.
35/67
time
 Cognitive Radio Technologies, 2007
Exact Potential Game Forms
• Many exact potential games can be recognized
by the form of the utility function
36/67
 Cognitive Radio Technologies, 2007
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
37/67
 Cognitive Radio Technologies, 2007
Interference Reducing
Networks
• Concept
– Cognitive radio network is a potential game with a potential
function that is negation of observed network interference
• Definition
   
 I  
i
i N
• Implementation:
()
– A network of cognitive radios where each adaptation
decreases the sum of each radio’s observed interference is an
IRN
time
– Design DFS algorithms such that network is a potential game
38/67
with   -V
 Cognitive Radio Technologies, 2007
Bilateral Symmetric
Interference
• Two cognitive radios, j,kN, exhibit bilateral
symmetric interference if
g jk p j    j ,  k   g kj p 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,
•    k ,  j  - the fraction of radio
k’s signal that radio j cannot
exclude via processing
(perhaps via filtering,
despreading, or MUD
techniques).
j

 j   j ,  k   k
What’s good for the goose, is
good for the gander…
Source: http://radio.weblogs.com/0120124/Graphics/geese2.jpg
 Cognitive Radio Technologies, 2007
39/67
Bilateral Symmetric Interference Implies
an Interference Reducing Network
• Cognitive Radio Goal: u     I      g
• By bilateral symmetric interference
i
i
ji
p j   i , 
j

j N \ i
g ki p k   k ,  i   g ik p i   i ,  k   b ki  k ,  i   bik  i ,  k 
• Rewrite goal
ui    

bik   i ,  k 
kN \i
• Therefore a BSI game (Si =0)
V     
i 1
g
ki
p k   k ,  i 
i N k  1
• Interference Function       2V   
• Therefore profitable unilateral deviations increase V
and decrease () – an IRN
40/67
 Cognitive Radio Technologies, 2007
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
S ta rt
power
ui  f
   Ii  f    
g ki p k 
L iste n o n
C hannel LC
R T S /C T S
e n e rg y d e te c te d ?
y
n

 fi ,
fk

N o te a d d re ss
o f a cce ss
node, a
P ick ch a n n e l to
liste n o n , L C
U p d a te
in te rfe re n c e
ta b le
 fi , fk 
kN \i
1

0
n
fi  fk
fi  fk
g jk p j  f j , f k   g kj p k   f k , f j 
M e a su re p o w e r
o f a cce ss n o d e
in m e ssa g e , p
 Cognitive Radio Technologies, 2007
T im e fo r d e cisio n ?
y
U se 8 0 2 .1 1 h
to sig n a l ch a n g e
in O C to clie n ts
A p p ly d e c isio n
crite ria fo r n e w
o p e ra tin g
ch a n n e l, O C
41/67
Statistics
Reduction in Net Interference
70
60
•
R educ tion in N et Interferenc e (dB )
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
Asynchronous
Round-robin
Legacy Devices
50
40
30
20
10
0
0
10
20
30
40
50
60
70
80
90
100
N um ber of A c c es s N odes
Reduction in Net Interference
42/67
 Cognitive Radio Technologies, 2007
Ad-hoc Network
• Possible to adjust
previous algorithm to
not favor access
nodes over clients
• Suitable for ad-hoc
networks
43/67
 Cognitive Radio Technologies, 2007
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/
 Cognitive Radio Technologies, 2007
44/67
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
45/67
 Cognitive Radio Technologies, 2007
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
46/67
 Cognitive Radio Technologies, 2007
Commercial Cognitive Radio
Standards
802.11h,y,
802.16h, 802.22
47
802.11j – Policy Based
Radio
2.4 GHz
• 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 2.48
Europe 2.402 2.48
Japan
2.473 2.495
Spain
2.447 2.473
France 2.448 2.482
5 GHz
US
UNII Low 5.15 – 5.25 (4) 50 mW
UNII Middle 5.25 – 5.35 (4) 250 mW
UNII Upper 5.725-5.825 (4) 1 W
5.47 – 5.725 GHz released in Nov 2003
Europe
5.15-5.35 200 mW
5.47-5.725 1 W
Japan
4.9-5.091
48/67
5.15-5.25 (10 mW/MHz) unlicensed
 Cognitive Radio Technologies, 2007
802.11e – Almost Cognitive
• 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)
49/67
 Cognitive Radio Technologies, 2007
802.11h – Unintentionally
Cognitive
•
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
 Cognitive Radio Technologies, 2007
50/67
802.11h: A simple cognitive radio
Observe
–
–
Must estimate channel characteristics (TPC)
Must measure spectrum (DFS)
Orientation
Orient
a) Radar present?
b) In band with satellite??
c) Bad channel?
d) Other WLANs?
Observe
Decision
–
–
–
Implement decision
Learn
–
Learn
Change frequency
Change power
Nothing
Action
Decide
Act
Outside
World
Not in standard, but most implementations should learn the environment to
address intermittent signals
51/67
 Cognitive Radio Technologies, 2007
IEEE 802.22
• 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
52/67
 Cognitive Radio Technologies, 2007
802.22 Status and Objectives
Objectives
Status
• Specify PHY and MAC
• 10 proposals merged
for fixed point-tomultipoint wireless
into 1 draft proposal at
regional area networks
March Plenary (March
operating in the
VHF/UHF TV broadcast
5-10, Denver CO)
bands between 54 MHz
and 862 MHz.
• Still working on
• Strict non-interference
bringing to ballot
with incumbent licensed
services.
• Aimed at bringing
broadband access in
rural and remote areas
53/67
PAR: http://www.ieee802.org/22/802-22_PAR.pdf
 Cognitive Radio Technologies, 2007
802.22 Deployment Scenario
• Devices
– Base Station (BS)
– Customer Premise Equipment
(CPE)
• Master/Slave relation
– BS is master
– CPE slave
• Max Transmit CPE 4W
54/67
 Cognitive Radio Technologies, 2007
Figure from: IEEE 802.22-06/0005r1
Proposed PHY Features of
802.22
•
•
•
•
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
55/67
 Cognitive Radio Technologies, 2007
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
56/67
 Cognitive Radio Technologies, 2007
Cognitive Aspects of 802.22
• 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
57/67
C. Cordeiro, L. Challapali, D. Birru, S. Shankar, “IEEE 802.22: The First Worldwide Wireless Standard based on Cognitive Radios,”

Cognitive
Radio
Technologies,
2007
IEEE DySPAN2005, Nov 8-11, 2005 Baltimore, MD.
Sensing Aspects of 802.22
• Region based sensing
C P E N um ber = 400, IT N um ber = 4
100
– Remote aided sensing
90
• Algorithm:
80
G rid Index Y
– Partition cell into disjoint
regions
– For each region assign a
remote (Customer
Premise Equipment)
• Example considered
squares with 500 m
sides
70
60
50
40
30
20
10
0
0
10
20
– CPE feeds back what it
finds
• Number of incumbents
• Occupied bands
 Cognitive Radio Technologies, 2007
30
40
50
60
70
80
90
100
G rid Index X
Source: IEEE 802.22-06/0048r0
58/67
802.16h
•
Draft to ballot Oct 06,
67% approve, resolving
comments)
•
Improved Coexistence
Mechanisms for LicenseExempt 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.
59/67
 Cognitive Radio Technologies, 2007
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
60/67
 Cognitive Radio Technologies, 2007
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
61/67
 Cognitive Radio Technologies, 2007
(fuzziness in original)
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
62/67
Wireless Access Systems Amendment for Improved Coexistence
 Cognitive Radio Technologies, 2007
Mechanisms for License-Exempt Operation, 2006-03-29
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
• 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
– Bid by tokens
63/67
 Cognitive Radio Technologies, 2007
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.
64/67
 Cognitive Radio Technologies, 2007
802.11y
•
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
 Cognitive Radio Technologies,
Source: 2007
IEEE
65/67
802.11-06/0YYYr0
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
IP or
Ethernet
• 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
 Cognitive Radio Technologies, 2007
66/67
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
67/67
 Cognitive Radio Technologies, 2007
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Cognitive Radio Technologies and WANN