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Understanding the issues in Software Defined Cognitive Radio

Slides are from

Prof Reed & Prof Bostian

(Virginia Tech) CR Tutorial

What you will learn

� Basic concepts of software defined radio

� Basic concepts of cognitive radio and its relationship to SDR

� How cognitive radios are implemented

� Analyzing cognitive radio behavior and performance

� Regulatory issues in cognitive radio deployment

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Software Defined Radio (SDR)

� Term was coined by Mitola in 1992

� Radio’s physical layer behavior is primarily defined in

software

� Accepts fully programmable traffic & control

information

� Supports broad range of frequencies, air interfaces

and application software

� Changes its initial configuration to satisfy user

requirements

Software Defined Radio Levels

� Highest level of reconfigurability

– Completely flexible modulation format protocols

and user functions

– Flexible bandwidths and center frequency i.e. RF

front end is also configurable

– Adapts to different network and air interfaces

– Open architecture for expansion and

modifications

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Software Defined Radio Levels

� Lowest level of reconfiguration

– Radio not easily changed

– Preset signal bandwidth and center frequency

– Few and preset modulation formats, protocols,

and user functions

Advantages of SDR

� Reduced content of expensive custom silicon

� Reduce parts inventory

� Ride declining prices in computing components

� DSP can compensate for imperfections in RF

components, allowing cheaper components to be

used.

� Open architecture allows multiple vendors

� Maintainability enhanced

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Drawbacks of SDR

� Power consumption

� Security

� Cost

� Software reliability

� Keeping up with higher data rates

� Fear of the unknown

� Both subscriber and base units should be SDR for maximum benefit.

Applications for SDR

� Military– Full connectivity

– Sensor Networks

– Better Performance

� Commercial– Lower cost – subscriber unit

– Lower cost – base unit

– Lower cost – network

– Better performance

� Regulatory– Stretch expensive spectrum

– Build in innovation mechanisms

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How’s Software Defined Radio different from other radios? –Application

How’s Software Defined Radio Different from other radios? – Design

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How’s Software Defined Radio different from other radios?- Upgrade Cycle

Cognitive Radio Concepts

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Cognitive Radio

� Term coined by Mitola in 1999

� Mitola’s definition:

– Software radio that is aware of its environment and its capabilities

– Alters its physical layer behavior

– Capable of following complex adaptation strategies

� A radio or system that senses, and is aware of its operational environment and can dynamically and autonomously adjust its radio operating parameters accordingly

� Learns from previous experiences

� Deals with situations not planned at the initial time of design.

What is a Cognitive Radio?

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Cognitive Radio

� Cognitive radios are machines that sense their environment (the spectrum) and respond intelligently to it

� Like animals and people, they– Seek their own kind (other radios with which they want to

communicate)

– Avoids or outwit enemies (interfering radios)

– Find a place to live (usable spectrum)

– Conform to the etiquette of their society (the FCC)

– Make a living (deliver the services that their users want)

– Deal with entirely new situations and learn from experience

Cognitive Radio is a powerful tool for solving 2 major problems: access to frequencies

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Cognitive Radio platforms is a powerful tool for solving 2 major problems: interoperability

Levels of Radio Functionality

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What is a cognitive radio?

Relationship between the cognition and the levels of functionality

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Cognitive Radio Advantages

� All of the benefits of software defined radio

� Improved link performance– Adapt away from bad channels

– Increase data rate on good channels

� Improved spectrum utilization– Fill in unused spectrum

– Move away from overoccupied spectrum

� New business propositions– High speed internet in rural areas

– High data rate application networks (e.g. video conferencing)

� Significant interest from FCC, DoD– Posssible use in TV band refarming

Cognitive Radio Drawbacks

� All the software radio drawbacks

� Significant research to realize

– Information collection and modeling

– Decision processes

– Learning processes

– Hardware support

� Regulatory concerns

� Loss of control

� Fear of undesirable adaptations

– Need someway to ensure that adaptations yield desirable networks

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Cognitive Radio & SDR

� SDR’s impact on the wireless world is dfficult to predict

� Some believe SDR is not necessary for cognitive radio

– Cognition is a function of higher layer application

� Cognitive radio without SDR is limited– Underlying radio should be highly adaptive

� Wide QoS range

� Better suited to deal with new standards

� Better suited for cross-layer optimization

Types of Software Defined Cognitive Radios

� Policy-based Radio

� Reconfigurable Radio

� Cognitive Radio

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Policy-based Radio

� A radio that is governed by a predetermined set of rules for

choosing between different predefined waveforms

� The definition and implementation of these rules can be

– During the manufacturing process

– During configuration of a device by the user

– During over the air-provisioning; and/or

– By over the air control

� Analogous to rules of what to order fro a menu

– I’ll have GSM today

Reconfigurable Radio

� A radio whose hardware functionality can be

changed under software control

� Reconfiguration control of such radios may involve

any element of the communication network

� Analogous to rules of what to order from a menu and

permit substitutions to the order

– I’ll have GSM today with 802.11 FEC

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Technology challenges of SDR

Radio Architecture

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Behind the converters: the software architecture

� Nature of architecture depends on applications: military, commercial

� Benefits of a good architecture– Clear way to implement system

– Reuse – modularity

– Quality control and testing

– Portability – one radio to another

– Upgradability

– Outsourcing/managing development

– Language independence

– More potential for over the air programming

– Standardized interfaces

� Middleware-based architectures are commonly used.

Implementing a SDR with the GNU Radio

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USRP

Challenges in SDR Design

� Hardware– Significant effort in computing HW

– Advance DSP Designs

– Flexible RF and antennas

– Flexible ADCs

– Tradeoff of performance and flexibility

� Software– Integration of components into single design flow

– Tradeoff of performance and flexibility

� Testing and validation– FCC hardware/software certification

– Smoothing of design cycle� Reduce overall time-to-market

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Technology Challenges of SDR

� Technology in SDR partitioned into 3 basic pieces

– Hardware

� Physical devices on which processing is performed or interface

to the real world

– Software

� Glue holding together system

– Network

� Functionality and ultimate value to the end user

� Advances needed in all 3 arenas

Hardware

� Significatn effort to date in computing HW

– Non-traditional computing platforms

– Advanced DSP designs

– High data rate FEC remains problematic

� Emphasis on computing HW alone can be myopic

– Other critical areas that require significant further work

� Flexible RF

� Flexible ADC

� Antennas

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Flexible RF

� RF is one of the main limiting factors on system

design

– Places fundamental limits on the signal characteristics

� BW, SNR, linearity

– Truly flexible SDR requires flexible RF

� Difficult task

– RF is fundamentally analog and requires different approach for the management of attributes

� One method for achieving this is through the use of MEMS

ADC Challenges

� ADC is the bound between analog and digital world

� SDR requires the tuning of ADC characteristics

– No of bits

� Support adequate SNR and dynamic range

– Sampling rate

� Prevent over-sampling

� ADC technology trends are not necessarily

compatible with these needs.

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ADC getting better

Integration of Hardware

� DSP share traits with GPP

– Similar programming methods

– Similar computing concepts

� Even though implementation may be widely different

� FPGA and CCM do not share these traits with GPP

– Completely different programming paradigm

– Portability is an extremely difficult problem

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So how do you make a software radio?

What kind of software is needed?

� Something to manage the hardware

– Configure associated devices

� Set devices to known states

– Initialize cores

� Make sure programmable devices are ready

– Set memory pointers in DSP

– Set FPGA to known state

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What kind of software is needed?

� Some standardized way of storing relevant

information

– More than just short-term memory

� Store configuration files

� Store last state of the machine

� Store user-defined attributes

– Identity

– permissions

– Should be able to map any kind of storage device to this

� Dynamic RAM, hard drive, FLASH, other

What kind of software is needed?

� Some way of structuring the waveforms

– Standardized way of structuring applications so that the

radio can run them

� In a window’s machine, these are .exec files

– It has to be generic enough for it to fit well with machines

other than GPPs.

� Needs to be able to interface with functional software

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What kind of software is needed?

� Something to actually run waveforms

– Install functional software in appropriate core

– Generate a start event

� Something to keep track of what is available and

what can and can’t be installed

– Ideally, this will bind the whole thing together

Fundamental composition of the SCA

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Radio TX Channel Statistics

Cognitive Engine

Radio RX

“Meters”“Old Knobs

Settings”

“Old Knobs

Settings”

Radio Parameters

“Knobs and Meters”

“Optimized Solution”

“New Settings” “New Settings”

CR reads the meters and turns the knobs.

Cognitive Engine

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Knobs

–Transmit power

– Modulation

– Coding

– Symbol rate

– Spectrum shaping

– Spreading

– Antenna Beamforming

– Etc.

Meters

–Bit error rate (BER)

– Frame error rate (FER)

– Signal power

– Battery life

– Computational resources

–Etc.

3/3/2008

Knobs and Meters

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The cognitive engine

� Intelligent agent that manages cognition tasks in a cognitive radio

� Independent entity that oversees cognitive operations

� Ideal characteristics

– Intelligence (accurate decisions)

– Reliability (consistent decisions)

– Awareness(informed decisions)

– Adaptability (situations dependent decisions)

– Efffciency (low overhead decisions)

– Excellent QoS (good decisions)

� Tradeoffs exist between these characteristics

CWT Two-Loop Cognition Cycle

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Environment awareness and evolving knowledge lead to optimal radio reconfiguration

–Inner loop: Learning

–Outer loop: Recognition and Adaptation

3/3/2008

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Distributed CE Architecture

493/3/2008

Analyzing performance in a cognitive radio

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Ways of analyzing performance

� For the cognitive radio

– QoS, detection of primary users (PU), SW

platform, QoS of PU, position location

� For the network of cognitive radios

– Quantifying the impact of the use of CR in a

network

– Game theorectic approach

Cognitive Radio Performance Evaluation:Q0S

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Cognitive Radio Performance Evaluation: Detection of Primary Users

Cognitive Radio Performance Evaluation: Underlying Software Radio Platform

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Cognitive Radio Performance Evaluation: Position Location

Cognitive Radio Performance Evaluation: Primary User’s QoS

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Dynamic Cognitive Radios in a Network

Need to have useful coordination

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Policy Issues

Policy Issues

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Traffic Model Analogy

Traffic Model Analogy

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Traffic Model Analogy