Instructor: Dr.George Collins

klapdorothypondMobile - Wireless

Nov 23, 2013 (3 years and 6 months ago)

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Instructor:
Dr.George

Collins


NIREESHA NAMBURU


Cognitive radio architecture


Cognitive engine design


Components descriptions


1.sensors


2.optimizer


3.decison maker


4.policy engine


5.radio framework


6.user interface


7.cognitive controller configuration


AI and its techniques


Conclusion


References





Operational cognitive radio platform

Cognitive
engine

Policy
engine

Networking/
radio
communicat
ions system


User domain

Policy
domain

Environmen
t & RF
channel



Cognitive

controller

User interface

sensors

optimization
n

Decision
maker

Policy
verification

Radio
framework

PSCR

CR GUI

Energy
detector

Signal class

meters

Knowledge
base

SQL
database

GNU radio

IRIS

KUAR

WSGA

Fuzzy logic

Rule based

WSGA verifier

XG


Sensors collect data from radio or other systems to
describe and model the environment.


The important aspect of a sensor is having a standard
approach to how data is transferred to a cognitive
controller.


Application programming interface(API)



Initialization


Waiting for data request from cognitive controller


Collecting data and building a model


Transferring model to cognitive controller



Cognitive engine sends
information to the sensor
through some generic
interface


Sockets and SOAP :
communicate information
between software
programs


Functions and processing
algorithms are retrieved
through external library




Sensor state machine

Interface
description

Data collection
library

XML modelling

Sockets,
SOAP,etc

External
application
,library etc


<?xml version=“1.0”?>

<sensor>

<model
-
name>”model
-
name”<
\
model
-
name>

<data
-
tag type=“type” size=“size” unit=“unit”>”value”<
\
data
-
tag>

…….

<
\
sensor>


the optimization process takes the user oriented information
from sensors or user interface to select or design a waveform
that will maximize the performance.


Optimizer produces waveform that comes close to the
QoS

values with respect to the provided environmental data.


Depending on the implementation the optimizer may build a
new waveform or select it from a list of predefined waveforms.



It coordinates information and decides how to optimize and act.


If optimization is required the decision maker will provide
some context such as optimization goal or time limit for when a
new waveform is required.


The current method of decision making is based on CBDT.


CBDT keeps database of observed cases ,the action taken to
respond to those cases and results of the action.


The policy engine must test and authenticate a waveform.


Two main goals of policy engines

1)
policy engine must be secure such that unauthorized
waveforms cannot be transmitted.

2)
It must be liberal enough to allow many different types of
waveforms to run on the system.


It is a component that translates between cognitive engine and
radio platform.


When the cognitive engine wants to reconfigure the radio’s
waveform it uses generic communication theory representation
in XML.


The mapping between the XML format to radio specific format
is done by parsing the XML file from cognitive engine and
formatting commands used to configure the radio.







The XML parser block is the translation block.


The SDR control can also be accomplished by external
interface such as through HTTP, message passing etc.


The radio framework used in this work is GNU radio software
radio.


Cognitive
engine

XML
implementa
tion file

Xml C++

Parser python


java

Radio
platform

(SDR)


It has widely varying responsibilities depending on the
cognitive radio use case.


Different instances

1)
Control window

2)
Simple configuration window


In most idealist view of cognitive radio there is no user
interface.


The important aspect of cognitive controller is its ability to use
many different implementations of the components described
above.


It is configured through an XML file that defines which
components are currently attached.


The cognitive controller can define and connect to multiple
sensors.


Each component is described by a specific name that the
cognitive radio uses to identify when collecting the
information.


Successful cognitive radios are aware ,can learn, and can take
action for any situation that might araise.These radios require
highly sophisticated learning and decision making capabilities.


Techniques

1)
Neural networks

2)
HMM

3)
Fuzzy logic

4)
Evolutionary algorithms

5)
Case based reasoning


The cognitive engine concepts were introduced and its
implementation was shown. The major components of the
platform include sensors,optimizer,decision maker, policy
engine, radio framework, user interface. The discussion mostly
focused on defining the roles and responsibilities of each
component to provide the context from which to build a
cognitive radio. Various AI techniques were discussed.


J.Mitola and G. Q. Maguire,Jr., “cognitive radio: making software
radios more personal,”IEEE proc. Personal communications,vol.
6,1999,pp.13
-
18.


T.W.Rondeau, C.W.Bostian, D.Maldonado, A. Ferguson,
S.Ball,B.Le, and S.Midkiff,”cognitive radio in public safety and
spectrum management, "telecommunications policy and research
conference,vol.33,sep.2005


FCC,”Implementing a Nation wide, Broadband , Interoperable public
safety network in the 700MHz band, "Federal communications
commision,Tech Rep. PS Docket No.06
-
229, Dec. 2006.


http://scholar.lib.vt.edu/theses/available/etd
-
10052007
-
081332/unrestricted/rondeau
-
dissertation.pdf