cognitive radio yves lacerte rockwell collins [email protected] (952) 826-0080
TRANSCRIPT
Cognitive Radio
Yves LaCerteRockwell [email protected](952) 826-0080
System Integration
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Topics
What is System Integration?
An Example - Cognitive Radio
Integration Trends
What is System Integration?
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INCOSE SE Handbook….
…establishment of system interfaces, internal and external……emphasis on risk management and continuous verification…
The process of putting a system together, with techniques to ensure all the parts work as a whole.
Integration is Hard
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Generally, the main contractor for the project is responsible for systems integration.
The sub-contractors will usually be part of the integration team.
Integration is one of the most costly and time-consuming activities in the systems engineering process.
For large and complex systems, up to 40% of the development effort may be used in this activity, mostly in system testing.
Cognitive Radio
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A Non-traditional
System Integration Challenge
Scientific American, February, 2006 http://www.sciam.com/article.cfm?id=000C7B72-2374-13F6-A37483414B7F0000“A Public Safety Cognitive Radio Node” http://www.sdrforum.org/SDR08/3.3-2.pdf “A Policy Proposal to Enable Cognitive Radio for Public Safety and Industry in the Land Mobile Radio Bands ”, http://www.netcityengineering.com/PID354224.pdf
Scenarios
Urban agencies need to communicate with each otherNew York City police and fire departments
during 9/11 were not successful
Federal, state and local level responders need to communicate Katrina response was less than successful
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The Problem
“Spectrum“ is regulated (e.g. FCC)Assigned/licensed
to users On a long term
basis For large regions
like whole countries
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A Solution
Cognitive RadioSenses and is aware of its environmentDynamically adapts to utilize changing radio
resources Maintains connectivity with its peers Does not interfere with licensed users and
other CRs
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Timeline
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2003 2004 2005 2006 2007 2008
DARPA’s
Demonstrationswithin 1 year
Commercial
viabilityexploration &
commercial
analysis underexisting
agreements
Viability
demonstratedfor commercial
purposes
within 2 year
SDR Forum can
initiate early workand insert into
standards bodies as
work matures
5 years for
etiquettesto be formally
standardized
2003 2004 2005 2006 2007 2008
CR Architecture
Networked Device
AntennaCoupling
Data Modem
ProcessorTransmitter
and Receiver
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Basic Non-Cognitive Radio Architecture:
Wireless Data Transceiver Subsystem Module
Spectrum Scanning and Interference Avoidance Module
Data ModemProcessor
Networked Device
Scanning Engine
SpectrumAnalysisEngine
Channel Pooling Server
Transmitterand Receiver
Antenna Sharing Module
Data ModemProcessorTransmitter
and Receiver
Cognitive Radio architecture:
Integration Challenge I
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Multi-disciplines Major Domains
Wireless communicationsLocation-aware sensors
Radio engineeringWide band antennas
Machine learning
Spectrum regulations
Application service
Etc.
Policy domain
Radio domain
User domain
Machine Learning
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Some tasks cannot be defined well except by example.
Discovers important relationships and correlations in large data sets.
The working environment is not be completely known at design time.
Mitola, “Cognitive Radio for Flexible Mobile Multimedia Communications”, IEEE Mobile Multimedia Conference, 1999, pp3-10
OrientEstablish Priority
PlanNormal
Generate Alternatives(Program Generation)Evaluate Alternatives
Register to Current Time
DecideAlternate Resources
Initiate Process(es)(Isochronism Is Key)
Act
Learn
Save Global States
Set DisplaySend a Message
ObserveReceive a Message
Read Buttons
OutsideWorld
NewStates
The Cognition Cycle
PriorStates
Pre-process
Parse
ImmediateUrgent
Infer on Context Hierarchy
Advantages
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Flexibility
A more flexible radio over classic radio systems.
Software makes it easier to upgrade for better performance…. And upgrade for new performance….
Cheaper RF Front-End Design
One problem with classic RF design is the complexity and the labor in developing a reliable design. With the design of a reliable Software Defined Radio (SDR), the quality and performance of the SDR can be enhanced by the digital hardware in order to reduce the complexity (and therefore the cost) of the RF front-end.
Digital Signal Processor (DSP), Field Programmable Gate-Array (FPGA), General Purpose Processor (GPP)
Smaller Parts Count
With a less complicated RF front-end, the total parts needed is simplified. With digital components like the DSP and FPGA taking the place of many passive and active components, the list is smaller and cheaper.
Disadvantages
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Software Reliability
Security
SWaP
Integration Challenge II Unlike traditional interferers, cognitive radios adapt their
operation in response to their perceived interference environment. When numerous cognitive radios are collocated, this interference environment may be constantly changing as the cognitive radios adapt to the other cognitive radios adaptations. Because of this recursive process, serious concerns are introduced: Under what conditions will the recursions settle down to a steady
state? What is that steady-state? Will the resources be hoarded by a single radio/link or will they
be equitably shared among the radios? Will the cognitive radios actually make use of available spectrum
without impinging on other radios’ spectrum rights? How much bandwidth will be consumed with signaling overhead
and how much bandwidth will actually be used for data transfer?
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A Typical Integration Example
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Collect Hardware
Components
Integrate Hardware Platform
Collect Software
Components
Integrate Software on
Target Hardware
Test System
InterfacesInterfaces
ConfigurationsConfigurations
Stress
User Acceptance
Test
Resolve Issues
Factory Acceptance
Human Systems Integration
Human Systems Integration
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Integration Trends
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Integrated Modular Architecture
Each supplier generally has proprietary hardware (LRU) increasing cost of supply / repair chain and aircraft weight
All software in a LRU/card must be developed to the same safety level even, if this is not strictly necessary, and is dedicated to that LRU
If the hardware platform changes the whole product needs to re-verified by licensing authority
Integration Trends
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Integrated Modular Architecture
Uses spare computing capacity to run multiple independent applications in a central processing network – fewer equipment racks therefore less weight
Application software is independent of an open architecture core executive – therefore it is platform and location independent
Application software can be validated independently of the core executive and hardware
Application software is location independent of the IO (Desirable but not always the case)
Integration Trends
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Micro and Nano Technologies
“The principles of physics, as far as I can see, do not speak against the possibility of maneuvering things atom by atom. It is not an attempt to violate any laws; it is something, in principle, that can be done; but in practice, it has not been done because we are too big”.
Richard Feynman, “There’s Plenty of room at the bottom: An invitation to enter a new field of physics,” Engineering and Science, Feb. 1960, http://www.zyvex.com/nanotech/feynman.html
Inductance Behaviors
Optical Thermal
Integration Trends
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Micro and Nano Technologies
Systems engineering will become a key enabler for the successful commercialization of multi-functional, micro and nano technologies (MNT). Systems engineering delivers the methodologies, processes and tools to enable the efficient integration and exploitation of these disruptive technologies.
Mechanical Fluidic
MEMS Design Flow
Analog Materials
CMOS Digital
BiPolar Parasitics
VLSI Design Flow
IntegrationIntegration
Integration Trends
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HW / SW Codesign
Increasing behavioral complexities… requires “design” optimizationmany functions, great variability, high flexibilityheterogeneous target systems - processors, ASICs, FPGAs, systems-on-chip, …many design goalsperformance, cost, power consumption, reliability, ...
Integration Trends
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HW / SW Codesign
Systems engineering will become a key enabler for the successful commercialization of complex embedded software intensive systems. Systems engineering delivers the methodologies, processes and tools to enable the efficient integration and exploitation of these disruptive technologies.
Enterprise Integration
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Enterprise Integration
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Business integration design and modeling of business processes
Presentation integration integration of corporate knowledge and business processes
Data integration how data is modeled and the meaning of the data
Control integration messaging between applications
Application integration different applications work together using mechanisms such as automatic event notification, flow control, and content routing
Enterprise Integration
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Integrating Two Systems
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Integration is Hard
High degree of uncertainty
Design for integrability
Integration strategies
Emergent properties
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Uncertainties
System components are not available on time
Duration of integration is longer than planned
Cost of testing facilities is higher than planned
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Integration Planning
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RequirementsSpecification
SystemSpecification
SystemDesign
DetailedDesign
Factory Acceptance
Test
SystemIntegration Test
Sub-system Integration Test
Factory Acceptance
Test Plan
System Integration Test Plan
Sub-system Integration Test Plan
User Acceptance
Test Plan
User Acceptance
Test
Component Implementation
Component Test
Design for Integrability
Integration tends to be more successful with low coupling between components
Partitioning decisions are made early, often without integration in mind
Hardware software co-design Merged integration approach
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Integration Strategies
StrategiesBig bang or IncrementalHorizontal or Vertical
Order of integration impacts efficiencyFirst come first integrated?Foundational components with long lead
time?
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Integration Strategy
Incremental integrationScheduling and staging strategy Components are developed at different
times or rates, and integrated as they are completed
The alternative to incremental development is to develop the entire system with a "big bang" integration
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Integration Strategy
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Sub-system 1 Sub-system 2
Component 1
Sub-system n
Sub-system 2
Component 2
Component m
Integration Strategy
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Sub-system 1 Sub-system 2
Component 1
Sub-system n
Sub-system 2
Component 2
Component m
Component 1
Component 1
Emergent Properties
A new component is introduced and problems are foundIs it due to the relationship between the new
component and the existing system?Or does the new component cause the
existing system to be used in a different way?
Did problems with the system exist BEFORE the component was added?
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The State of Our Knowledge
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System “C”
We know quite a lot about integrating components (over which we may have little or no control) to form systems.
We know something about integrating individual systems (over which we may have little or no control) into systems of systems.
System “B”
We know very little about integrating an interoperable network of systems…the key distinction being that the network is unbounded (or very loosely bounded) and has no single controlling authority.
System “A”
“SYSTEM D”
Unplanned, unexpected, emergent behavior here…
Unbounded Systems
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E.g. Large-scale communication networks
Incompletely and imprecisely definedDistributed administrative control No central authorityLimited global effect
Emergent algorithms
Predict global effects based on local activities
Integration challenges
What guarantees can be provided that the results of integrating systems into larger systems, when the interfaces are not
completely known, will be acceptable? This is often addressed as the interoperability problem.
Interoperability
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Integration: the act of forming, coordinating, or blending into a functioning or unified whole.
Interoperation: The ability of two or more systems or components to exchange information and to use the information that has been exchanged.
Interest in integration of current stand-alone systems to meet future system requirements.
Driven by
advances in communication technology
recognition of common areas of functionality in related systems
increased awareness of how enhanced information access can lead to improved capability
Interoperability Challenges
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Communication Media
Wireless (WiFi, WiMax, cellphones) Secure? Reliable?
Messaging and Security
Across different equipment from different vendors:– Cyber security –“security by obscurity” is no longer feasible– Network management – will the data get where it needs to go in a timely manner?– Protocol standards – agreement on standardized interfaces between systems
Data Management
Across different equipment, vendors, customers– Vast amounts of data, data discovery – how to manage this data?– Data mining, data consistency, data privacy – how to find and validate data?– Conversion of “data” into “information” – how to use effectively?– Data modeling standards – ability for “self-healing”
Computer Applications
Real-time analysis?– Automated controls – what and where should they be implemented?– System reliability, efficiency, service, safety, compliance?
Game theory
Does the algorithm have a steady state? What are those steady states? Is the steady state(s) desirable? What restrictions need to be placed on
the decision update algorithm to ensure convergence?
Is the steady state(s) stable?
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