the future of cognitive radio - supélec future of cognitive radio ... mitola radio xml...

The Future of Cognitive RadioSupelec

Rennes, France12 May 2011

Dr. Joseph Mitola III, Fellow of the IEEEDistinguished Professor, School of Engineering and Science, Distinguished Professor, School of Engineering and Science,

Distinguished Professor, School of Systems and Enterprises, andVice President for the Research Enterprise

Stevens Institute of Technology

© 2011 Dr. Joseph Mitola III All Rights Reserved

The Future of Cognitive Radio

• Flexible Efficient Cost-Effective Devices– Nano-engineered, Wearable, Arrays of Everything

• Algorithms, Firmware, Software in Devices– “80%” Reuse with “80%” Reconfigurability– “80%” Reuse with “80%” Reconfigurability– Matlab to Commercial RF Devices in Days-Weeks– Platform Rehosting of Existing Code in Weeks

• Networks that Learn so User Doesn’t Have To– Integrate Heterogeneous RF Devices, Home, Work– Integrated Commercial Privacy and Security

2

Future Cognitive Radio Devices

• More Flexible Cost-Effective RF-IF Devices– Nano-engineered Linear Amplifier Circuits– Multiscale Control of RF-IF Properties

• Array-antenna Radio Access Points (RAP)– 400-800 MHz Low Density/Rural Broadband– 400-800 MHz Low Density/Rural Broadband– 60 GHz Indoor and Bluetooth

• Power Scavenging – Recovery• Massive Array Processing on Chip• Wearable Ensemble Replaces iPhone

– Augmented Vision, Hearing, Awareness, Memory

3

Environment

Cognitive Radio (DSA)Cognition Cycle

Cognition

EnvironmentSpace-TimePropagationNetwork

Meta-Software

Antenna RF Modem

INFOSECBasebandUser Interface

Equalizer Model

Variable Bindings

...

User(s)IdentityNeedsBehaviors ...

Self ModelBehaviorModels

User

Environment

Antenna RF Modem Baseband User Interface

Hardware

INFOSEC

Protocol Stack, ControlModem, Equalizer, etc.

Software RadioSoftware Modules …..

KnownSelf

4© 1997-2011 Dr. Joseph Mitola III All Rights Reserved

Mitola Radio XML ⇒⇒⇒⇒ Cognitive Linguistics Behavior Model (CLBM)

BasebandUser InterfaceVariable Bindings

Maguire: CR is Impossible

Because of Gödel

Simon Haykin

Dynamic Spectrum Access

Primary (Licensed) Spectrum

Cordless Telephones: Analog, DECT …

Unlicensed Spectrum (Part 15)

Space-time DynamicsNetwork Management

Overlay: OFDM Water Filling

Measurements © 2006 Shared Spectrum Company, Used with Permission

(DSA)

Cellular 1G 2G CDMA 3GPP

Underlay: Ultra Wide Band (UWB)

Noise Temperature

Cordless Telephones: Analog, DECT …WLAN: 802.11 a/b/b WiFi …WPAN: 802.15, BlueTooth, HomeRF


MaliciousAgents

US Whitespace MarketsPropelling CR

6

Bian and Park, Addressing The Hidden Incumbent Problem In 802.22 Networks SDR09

© 1997-2011 Dr. Joseph Mitola III All Rights Reserved

FCC

Digital Whitespace Simulation

7

© 2011 Jaap van de Beek, Janne Riihij¨arvi, Andreas Achtzehn, Petri Mahonen, DySPAN 2011, used with Permission

Improved Terrain Modeling• © Rohan Murty et al

SenseLess, DySPAN 2011• 70-80% Improvement in

white space via Longley Rice spatial modeling Rice spatial modeling with terrain

• White space today• Dynamics become more

intense over time• Precomputatons

8

Sensor-Validated RF Modeling


Compressive Sensing

10

J. N. Laska, W. F. Bradley, T. W. Rondeau, K. E. Nolan, and B. Vigoda, DySPAN11

Femtocell-Handset Sensing

Dynamic Spectrum Available[Riva Networks compact GSM]

Low Power, Building Shadowing, Creates GSM Reuse Op portunities

Fine Structure Sensing and ControlWiFi 1 Mbps VoIP Coverage (Green)

100 mW GSM GPRS (Blue) 25 kHz LMR Voice (1.2km Red)

© 1997-2011 Dr. Joseph Mitola III All Rights Reserved12

LTE Advanced MIMO Directional Control

x(t)

x(t-τ1)

y(t)

x(t-τ2)

1st Bit

2nd Bit

3rd Bit

© 1999 MIT Lincoln Laboratory Used with Permission

Multiple Element Subspace TrackingATT as vBLAST aka MIMO100 λλλλ Array for 16 λλλλ Cost3x to 10x “Shannon” CapacityCOST: 1000x MIPS (practical ~2013)

© 2007 Stephen Fast, Remcom


Directional Sensing

© 2006 Dr. Joseph Mitola III Used with Permission

Sensing Highlights

• DVB-T Field Trials and Tools (Philips)

• Shape-Based Signal Classification (Supelec)

• Wavelet Edge Detection (A*Star Singapore)

• Multi -stage Cross Layer (UCLA)• Multi -stage Cross Layer (UCLA)

• Distributed Cooperative Sensing (U Mich, Deutsche Telcom; Stevens)

• Sensor Network Business Case (Telenor)

• Sensing vs. Databases (Vrije U, IMEC)

15

Comprehensive Spectrum Sensing

© 2005 Shared Spectrum Company (Dr. Mark McHenry) Used with Permission, adapted by the author

Processing Gain

Antenna Gain

Duty Cycle

Policy ReasoningP

olicy Processing

Local Policy Repository

Active Policy Set

RF Environment Map

Data Sources

LocalSenso r

SensorNetworks Database

SpectrumUsage Info

Radio Info Base

•User & Radio ID•Location, Time•Status

Policy Statements from aPolicy Management Authority

-Downloadable- Securely Modifiable

RF Space-time Dynamics

TransmissionDecisions Requests

17

Policy P

rocessing

Policy Conformance Reasoner(PCR)

• Policy Decision Point

•Reasoning/Inference

• Conformance Checking

Control & Behavior Modeling

andReasoning

System Strategy Reasoner

Transmission Opportunity Requests/Replies

Policy Enforcer

Stored Transmission

Decision Replies (Approve or

Deny)

TX ControlCommands

TX ControlCommands

TX ControlReplies

Transmission Decision Refresh Request

TransmissionDecision RepliesTransmission

Decisions Replies


Meta-Languages

18

Shujun Li, Collaborative Optimization of Cognitive Radio Parameters Using Ontology and Policy Based Approach (Boston: Northeastern University) 18 Dec 2009


Spectrum Management Database

• Location, Radiated Power– Requirement to check the database

– Requirement to prevent harmful interference

• ATT NOI Response for Policy Radio• ATT NOI Response for Policy Radio“The FCC should proceed cautiously with any experimentation with policy radios out of concern for security, including the ability of end-users to hack the device and alter how it responds to policies”

19

Self Aware Networks

20

IBM Autonomic Network Challenge 2001 (traffic, time, power, CPNs, …)


Gödel Coding for Intel-JVM

Symbol Number Symbol Number Symbol Number

0 1 succ 3

¬¬¬¬ 5 ∨∨∨∨ 7 ∀∀∀∀ 9

21

Gödel Coding ααααS→→→→ N

¬¬¬¬ 5 ∨∨∨∨ 7 ∀∀∀∀ 9( 11 ) 13

Gödel Decoding N →→→→ ααααS

11*13 = 143 →→→→ ‘( )’ ∈∈∈∈ alphabet ααααS describes S∈∈∈∈ RCF

Fatal Flaw MathematicsPrimitive Recursive Functions (PRF)

Gödel 1934Kleene 1941Mitola 1999[19]

g. While and Until Loops embody the Flaw

22

General Recursive Functions (GRF)

DO I=1,10 IF X=10 Call Y

X = X+1END Loop


Turing-equivalent Security: Impossible

“This Sentence Is False”

If it’s true then it must be false, soMalware Goes

Sony Root Kit“Ignore me”

Stack Overflow“Do This”

Valuable Intellectual Property of Stevens Institute of Technology – No Further Disclosure

23

If it’s true then it must be false, soAssert it false, and infer that it is true so

Assert it true, then it is false, but …

Computers Loop

Forever

Malware Goes Here

Malware Goes Here This Computer Is Secure

This Network Is Secure


Lakoff-Jackendoff-Ziemke Cognitive Linguistics

< Bayi-Balan/>1

<Person/>

<Animal/> 1. In Dyirbal cultureculture, the

male and female cannot

be combined

Lakoff Basic Categories: Things

<Woman/>

<Frau/><Man/>

<Mensch/><Li/>

<Giraffe/> <Chair/>

Thingsare the fundamental neonatal gestaltsPlacesdefine interactions among things

Pathsassociate places in sequence for a purpose[Things moving down paths define actions]

[Things that initiate or constrain actions are causes]<Mommy/>

Experiential


Cognitive Linguistics Things


Cognitive Linguistics Behavior Model (CLBM)

Things “Everybody knows”

CLA first identifies the few universally common Thingsof a domain

Placesare the vector fields that characterize interaction possibilities for each Thing

Places “Near Field, BLOS”designate subspaces

Pathsare sequences of places through which action may occur

Paths “Multipath, MIMO”Basis for actions


Modeling Radio DynamicsAction is the movement of a Thing along a Path

Actions“TX, RX”Induces

What happened

Transmit: Signal-In-Space = Thing.new(Tower)Transmit: Signal-In-Space = Thing.new(Tower)

Causeis the Thing that initiates an Action

Causes“ETSI”

ConstrainsWho to fine

Air Interface * Channel State


Cognitive Linguistics Metaphors• Things [Lakoff-Jackendoff]

– Body experience of physical things: touch, eat, don’t eat, don’t touch• Mind metaphor: ideas, good ideas, bad ideas

• Places [Sensorimotor interaction with a Thing] Video Game– Body is container: eat/ defecate, drink/ urinate, feel good, get sick– Room is a container in which we are contained

• Activity is a place: goodness, success, failure, consequences– Non-visual space continues to exist: [certain] abstractions are real– Non-visual space continues to exist: [certain] abstractions are real

• Paths [partially ordered (<) set of Places] [Lakoff-Jackendoff]– Physical movement experience

• Activation is motion metaphor; Activity is journey (plan) metaphor

• Actions [Thing moving down a Path] [Mitola]– Anger as burden, dangerous animal, opponent, fire, heat

• Causes [Thing.Action that initiates or modulates Action] [Mitola]– Some Thing initiates {some [other] thing to move down a path}

• Reason via metaphor: bodily experience => internal experience => expertise => abstraction => logic, language as shared experience


CLTD Policy Things

29

[Professors Hong Man and Joe Mitola, IEEE Conference on Semantics 2009]CLTD: Cognitive Linguistics for Technical Domains


Heterogeneous Mobile Architecture

[Ari Ahtiainen et al SDR Forum 08ETSI TR 102 680 RRS Ref Arch]


Network On Chip Architectures

32

IMEC

TileraTile64

NVidiaGTX 28510 Clusters

3 Streaming Multiprocessors 8 P

roce

ssor

s


CL Model of HW-SW Signal Processing

Things “Everybody knows”

CL modeling first identifies the few universally common Things of a (sub) domain

Placesare the vector fields that characterize interaction possibilities for each Thing

33

Places “IO, Memory”indexed subspaces250MBps

Pathsinclude sequences of places through which action may occur

Paths “Signal Flow Graph”Basis for actions


CL Model of HW-SW DynamicsAction is the movement of a Thing along a Path

Actions“Load, Run”

Induces dynamic Things

Load

Load: Process[i] = Thing.new(Processor[j])[j,i]

34

“Abstract State Machine”Constrains

dynamic Things

Causeis the Thing that initiates or constrains an Action

CausesASM ASM

MSC


Semantic Waveform Portability


CognitiveLinguistics

CLBM Under the Hood

thing

36

Actions:Signal Things flow through Functional Paths via Input-Process-Output Places driven by Causal Events


UMD DIFSpiral CMU

OthersGNU Radio

Early Adopter

CampbellEnergy

Bowen

FAA

Meyerrose Amoroso Hathaway Wynne Mitola

Sachs

ISP

Levinshon

Finance

Privacy - Law

LTG Elder

Peake

Medical

Rodriguez

Hi Tech

Atkins

Net Centric

BG Davis

STRATCOM

McCarthy

INSC

Gong

Taiwan

Luiijf

TNO

LTC Jazri

Malaysia

Globalization

Fifty five speakers: Draft Policy Guidebook


Industry Cybersecurity Consensus

• Wireless Networks– Represent the most severe security requirements– Identity, QoS/ Denial of Service, User Emulation

• Critical Needs• Critical Needs– LTE-equivalent security standard for converged

wireless-core multimedia networks– Privacy-preserving identity-role[-situation agile?]

management – beyond Role Based Access Control

• CLBM for Secure Geospatial DSA

39

Conclusions• Radio Systems Engineering Perspective

– Systems Engineering Methods, Processes, Tools

⇒ Heterogeneous Observable, Controllable, Secure

• Global Collaboration– European, US, Asian Centers of Excellence– European, US, Asian Centers of Excellence

– Market, Social, Government Value

– Cybersecurity of Edge Networks and Devices

• Expanding Commercialization– Devices, Algorithms, Services with Security


References (1 of 3)1. George Lakoff, Women, Fire, and Dangerous Things ()19872. Ray Jackendoff,Semantics and Cognition, volume 8 of Current Studies in

Linguistics Series. MIT Press, Cambridge, Massachusetts 1983. 3. John R. Bender. 2001. Connecting language and vision using a conceptual

semantics, Master’s thesis, Massachusetts Institute of Technology.4. Keith Bonawitz, Anthony Kim, and Seth Tardiff, An Architecture for Word

Learning using Bidirectional Multimodal Structural AlignmentReport for NSF Award IIS-0218861 W03-0605.pdf (Cambridge, MA: MIT) 2003Award IIS-0218861 W03-0605.pdf (Cambridge, MA: MIT) 2003

5. Peter Gärdenfors, “Representing actions and functional properties in conceptual spaces,” Body, Language, Mind: EmbodimentT. Ziemke et al, Editors (Berlin: Mouton de Gruyter) 2007

6. M. Johnson and T. Rohrer “We are live creatures: Embodiment, American Pragmatism” in T. Ziemke, Ibid

7. John Koza, www.genetic-programming.org; Genetic Programming (Volumes 1 [92, MIT Press] through IV [Kluwer, 2003])

8. Jing Liu et al, “Moving Block Sequence and Organizational Evolutionary Algorithm for General Floorplanning with Arbitrarily Shaped Rectilinear Blocks” IEEE Trans Evolutionary Computation (NY: IEEE Press) Oct 08


References (2 of 3)9. John S. Powell, “Cognitive and Software Radio: A Public Safety Regulatory

Perspective” (nstpc.org) 2004 10. J. Mitola, Software Radio Architecture (NY: Wiley) 200011. J. Mitola, Cognitive Radio Architecture (NY: Wiley) 200612. W. Wayt Gibbs, “Autonomic Computing,” Scientific American (NY: Scientific

American) May 200213. Halimic et al, “Optimal Functional Mapping Onto End-To-End Reconfigurable 13. Halimic et al, “Optimal Functional Mapping Onto End-To-End Reconfigurable

(E2R) Equipment Hardware Platform,” Proc. SDR Forum Technical Conference 2006 (Orlando, FL: SDR Forum) 2006

14. Gary Rose, Wireless Broadband and the Redlining of Rural America (www.wirelessfuture.newamerica.net) April 2010

15. I. Suzuki et al, “Reduced Cluster Search ML Decoding for QO-STBC Systems” (Brazil: State University of Londrina) 2009

16. E. Bogenfeld & Ingo Gaspard "Self-x in Radio Access Networks,” E3 White Paper (Version 1.0, 2008-12-22) 2008


References (3 of 3)17. Dominique NUSSBAUM et al, “Open Platform For Prototyping Of Advanced

Software Defined Radio And Cognitive Radio Techniques,” Proc. 12th EuromicroConference on Digital System Design(NY: IEEE Press)2009

18. Erol Gelenbe et al, “Self-Aware Networks and QoS,” Proc. IEEE (NY: IEEE Press) Sep 2004


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