IRIS is a software architecture for cognitive radio networking testbeds that allows researchers to develop, test, and validate reconfigurable network designs. The architecture supports full runtime reconfiguration of radio system parameters. It uses a component-based approach where discrete signal processing functions are linked together to build receiver and transmitter chains. These components are contained within engines that manage their execution and reconfiguration. The example application shows how IRIS can be used to dynamically change modulation schemes based on channel conditions.

1. IRIS: An Architecture for Cognitive
Radio Networking Testbeds
Patricia Oniga

2. Contents
• Context
• Introduction to IRIS
• Architecture
• Example application
• Comparison with other platforms
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3. Context
• Cognitive Radio (CR)
“ a software defined radio (SDR) with a cognitive engine brain ”
– Capable of fully (self) reconfiguring radio system parameters
(waveform, operating frequency, protocol and networking)
• SDR – enabler technology for CR
– Software implementation of components traditionally
implemented in hardware (modulators, mixers, filters,
amplifiers, etc ..)
– computing device (GPP-based, DSP-based, FPGA-based) + RF
front end
– E.g: GNU Radio [1], OSSIE [2] (Open Source SCA
Implementation - Embedded), IRIS
[1] http://gnuradio.org/redmine/projects/gnuradio/wiki
[2] http://ossie.wireless.vt.edu/ 3

4. IRIS
• “Implementing Radio in Software”
• Software architecture for CR testbeds
• Develop, test, validate reconfigurable network
designs
• Design goal: support full runtime reconfiguration
• C++
• Runs on a variety of GPPs (x86, ARM, PowerPC) and
OSs
• Support for specialized processors (DSPs, CellBE),
dedicated hardware (FPGAs) as accelerators
• Support for higher layers: MAC, Network
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5. Reconfiguration Interface
Architecture (I)
• Component based Data passing Signal
interface … Processing …
• Components Function
– implement discrete signal processing functions
• e.g: digital filter, modulator etc ..
– reconfigurable – support for:
• Parametric reconfiguration – adjust component operation
• Structural reconfiguration – dataflow switching
– linked together to build RX and TX chains
QAM
… Scrambler symbol
mapper
OFDM
modulator …
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6. Architecture (II)
• Engines
– component “containers“
– manage execution, datapassing and reconfiguration
semantics of components
– Tradeoff between performance and flexibility
– Scheduled PHY Engine (sPHY) Flexibility
x fPHY
– Flexible PHY engine (fPHY) Net stack engine
x
– Network Stack Engine
– Radio – one or more engines x sPHY
Performance
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7. Architecture (III) – How does it work ?
• Triggers
– Internal reconfiguration triggers
• in response to a change detected by one of the radio
components
– External reconfiguration triggers
• From UI, new XML configuration documents passed to
the system
• Component events – support for triggers
• Controllers – listen and respond to events
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8. Architecture (IV)
Source: [3]
[3] Iris: An Architecture for Cognitive Radio Networking Testbeds 8

9. Example Application
Source: [3]
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10. Comparison with other platforms
Source: [3]
OSSIE - Open Source SCA Implementation – Embedded
SCA[4] - Software Communications Architecture
- Architecture framework - tells how elements of hardware and software are to
operate within a SDR
- used by US military’s Joint Tactical Radio System (JTRS)
[4] Software Communications Architecture 10

11. Thank you!
Questions?
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12. Comparison between IRIS engine
types
Characteristic Relation
Component type between
Operates Data Runtime
(reconfigurability input and
on flow Efficiency
Engine point of view) output data
type rates
Scheduled PHY Unidir
Not reconfigured Data
(sPHY) Fixed ection High
on a regular basis samples
al
Flexible PHY Unidir
Highly It is not Data
(fPHY) ection Lower
reconfigurable fixed samples
al
Network Stack
Engine Highly Bidirec
- Packets High
reconfigurable tional
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