Networking Cognitive Radios

1
Networking Cognitive Radios

• Interaction Problem
• Role of Policy
• Techniques for designing network
• Commercial standards

2
The Interaction Problem

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

3
Dynamic Spectrum Access Pitfall

• Suppose
• g31gtg21 g12gtg32 g23gtg13
• Without loss of generality
• g31, g12, g23 1
• g21, g32, g13 0.5
• Infinite Loop!
• 4,5,1,3,2,6,4,

2
3
1
Interference Characterization
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)
0 1 2 3 4 5 6 7
4
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

5
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
6
Network Analysis Objectives

1. Steady state characterization
2. Steady state performance
3. Convergence
4. Stability/Noise
5. Scalability

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?
7
Cognitive Radio Network Modeling Summary

• Radios
• Actions for each radio
• Observed Outcome Space
• Goals
• Decision Rules
• Timing

• i,j ?N, N n
• AA1?A2?????An
• O
• ujO?? (ujA??)
• djO?Ai (djA? Ai)
• TT1?T2?????Tn

8
Comments on Timing

• 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

• 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
• TT1?T2?????Tn
• t ? T

9
Variety of game models

• Normal Form Game ltN,A,uigt
• Synchronous play
• T is a singleton
• Perfect knowledge of action space, other players
  goals (called utility functions)
• Repeated Game ltN,A,ui,digt
• 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
  ltN,A,ui,di,Tgt
• 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

10
Cognitive radios are naturally modeled as players
in a game
Goal
Establish Priority
Immediate
Normal
Urgent
Outcome Space
\
Negotiate
Adapted From Mitola, Cognitive Radio for
Flexible Mobile Multimedia Communications , IEEE
Mobile Multimedia Conference, 1999, pp 3-10.
11
Interaction is naturally modeled as a game
Radio 1
Radio 2
Actions
Actions
Action Space
Decision Rules
Decision Rules
Informed by Communications Theory
u2
Outcome Space
u1
12
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)
13
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

14
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

15
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

9.6
7
16
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?

18
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 theres been an FCC
• Whats new is assuming decision makers are the
  radios instead of the people controlling the
  radios

19
Policy applied to radios instead of humans
mask

• 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.

frequency
Policies
20
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

21
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

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.
22
Designing Well-Behaved Cognitive Radio Networks

• Repeated Games, Potential Games, Markets

23
Repeated Games

• Same game is repeated
• Indefinitely
• Finitely
• Players consider discounted payoffs across
  multiple stages
• Stage k
• Expected value over all future stages

24
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
  radios 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.

25
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

C
N
Nada
-5,5
0,0
nada
-100,0
c
-1,1
5,-5
-100,-1
-100,-100
n
-1,-100
0,-100
26
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 Motivation, Explanation, and
Application to Power Control, Globecom2001, pp.
821-825.
27
Instability in Punishment

• Issues arise when radios arent 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
28
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

29
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

30
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 users channel
  goes up (down if when done)

31
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

32
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 gt 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)

33
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
From Y. Zhao, J. Gaeddert, K. Bae, J. Reed,
Radio Environment Map Enabled Situation-Aware
Cognitive Radio Learning Algorithms, SDR Forum
Technical Conference 2006.
34
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

35
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
36
Exact Potential Game Forms

• Many exact potential games can be recognized by
  the form of the utility function

37
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

38
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 radios
  observed interference is an IRN
• Implementation
• Design DFS algorithms such that network is a
  potential game with ? ? -V

?(?)
time
39
Bilateral Symmetric Interference

• Two cognitive radios, j,k?N, exhibit bilateral
  symmetric interference if

• ?k waveform of radio k
• pk - the transmission power of radio ks waveform
• gkj - link gain from the transmission source of
  radio ks signal to the point where radio j
  measures its interference,
• - the fraction of radio ks
  signal that radio j cannot exclude via processing
  (perhaps via filtering, despreading, or MUD
  techniques).

Whats good for the goose, is good for the gander
Source http//radio.weblogs.com/0120124/Graphics/
geese2.jpg
40
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

41
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

42
Statistics
Reduction in Net Interference

• 30 cognitive access nodes in European UNII bands
• Choose channel with lowest interference
• Random timing
• n3
• Random initial channels
• Randomly distributed positions over 1 km2

Asynchronous
Round-robin
Legacy Devices
Reduction in Net Interference
43
Ad-hoc Network

• Possible to adjust previous algorithm to not
  favor access nodes over clients
• Suitable for ad-hoc networks

44
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/

45
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 its a potential game when theres
  no externality to the trade

46
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 Standards

• 802.11h,y, 802.16h, 802.22

48
802.11j Policy Based Radio
2.4 GHz
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

• 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

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 5.15-5.25 (10 mW/MHz)
unlicensed
49
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)

50
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

51
802.11h A simple cognitive radio

• Observe
• Must estimate channel characteristics (TPC)
• Must measure spectrum (DFS)
• Orientation
• Radar present?
• In band with satellite??
• Bad channel?
• 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

Decide
Orient
Observe
Learn
Act
Outside World
52
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

53
802.22 Status and Objectives

• Objectives
• 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
54
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
55
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

56
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

57
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

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.
58
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
59
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.
60
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

61
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)
62
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
63
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

64
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.
65
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/u
  ls
• Must check for existing devices at same site

Source IEEE 802.11-06/0YYYr0
66
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
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