chapter 2shodhganga.inflibnet.ac.in/bitstream/10603/10204/10... · instantiate the right number of...

Chapter 2

Research Methodology

2.1 Introduction :

The chapter endeavors to provide technical background materials to

provide basis for understanding technologies viab le for development

of cognitive radio based networks tools used to design cognitive radio

based network are typically considered to be of two type (i) hardware

or SDR (software defined radio) with their ancil laries ( i i) software to

control network. First of al l we are going to discuss technologies

available for hardware design and development of cognitive radio .

The basic technologies used for

2.2 Software-defined radio (SDR):

SDR, is a radio communication system where components are

implemented by means of software on a personal computer or

embedded computing devices with minimal e lectronic hardware l ike

antenna, RC coupled circuits etc.

A basic SDR system can be made up of a general purpose

computing devices equipped with a sound card, or other analog -to-

digital converter, preceded by some form of Radio Frequency front

end (RFEE). Significant amounts of signal processing are handed over

to the general -purpose processor, rather than being done in special -

purpose hardware l ike FPGA or DSP.

Software-defined radio (SDR), refers to wireless

communication in which the transmitter modulation is ge nerated or

2. Research Methodology 15

defined by a software program and computing device , and the

receiver uses a computing devices and software to recover the signal .

To select the desired modulat ion type, the proper programs must be

run by computing system that control the transmitter and receiver.

The most significant asset of SDR is i t’s flexibil i ty and

dynamicity . Wireless systems employ protocols that vary from one

service to another. Even in the same typ e of service, for example

wireless fax; the protocol often differs between geographic locations .

A single SDR set with an all - inclusive software repertoire can be used

in any mode anywhere in the world. Changing the service type, the

mode, and/or the modulation protocol involves simply select ing and

launching the particular computer software .

The ult imate goal of SDR technology is to provide a single

radio transceiver capable of playing the roles of cordless tele phone,

cell phone, wireless fax , wireless e-mail system, pager, wireless

videoconferencing unit , wireless Web browser, Global Posit ioning

System (GPS) unit , and other functions st i l l in the realm of science

fict ion, operable from any location on the surface of the earth, and

perhaps in space as well .

2.3 SDR System Architecture:

Figure 2.1 i l lustrate an SDR-based wireless base station that

you can reconfigure to support multiple standards. To reconfigure the

entire system, an ideal SDR base stat ion has to perform all signal

processing tasks as digital signal processing. However, current -


generation wideband data converters are not capable to support the

processing bandwidth and dynamic range required across different

wireless s tandards. As a resul t , the analog -to-digi tal converter (ADC)

and the digital - to-analog converter (DAC) are usually operated at

intermediate frequency (IF) and separate wideband analog front ends

are used for subsequent signal processing to the radio frequency (RF)

stages, as shown in Figure 2.1

1. DUC: Digital up converter

2. CFR: Crest factor reduction

3. DPD: Digital pre distort ion

4. DDC: Digital down converter

5. PA: Power amplifier

6. LNA: Low noise amplifier


Figure 2.1 SDR Architecture Based on Current -Generation

Technology1

1 Courtsey ALTERA FPGA solution For SDR (www.altera.com/end-

markets/wireless/advanced-dsp/sdr/wir-sdr.html )


2.3.1 Digital IF Processing:

Digital IF extends the scope of digital signal processing (DSP)

beyond the baseband domain out to the antenna to the RF domain.

Digital IF processing increases the flexibil i ty of the system while

reducing implementation costs. Moreover, digital frequency

conversion provides greater flexibil i ty and higher performance than

tradit ional analog techniques. Altera Stratix®

series FPGAs, with their

high-performance embedded DSP blocks, Nios®

II embedded soft

processors, Tri Mat rix memory architecture, and high -speed

interfaces, provide a highly flexible and integrated platform to

implement computat ionally intensive digital IF functions including

digital up-down converters.

2.3.2 Digital Up converter:

Data formatting often required between the baseband processing

elements and the up converter can be seamlessly added at the front

end of the up converter, as shown in Figure 2.2. This technique

provides a fully customizable front end to the up converter and allows

for channelization of high-bandwidth input data, which is essential

part of many wireless system. Logic or a Nios II embedded processor

can be use to control the interface between the up converter and the

baseband processing element.


Figure 2 .2. Digital Up converter2

1. RRC = Root-raised cosine

2. NCO = Numerically controlled oscil lator




In digital up conversion, the input data is baseband fi l tered and

interpolated before i t is quadrature modulated with a tunab le carr ier

frequency. To implement the interpolating baseband finite impulse

response (FIR) fi l ter , Altera ‘s FIR Compiler can be use, which can

support optimal fixed or adaptive fi l ter architectures can be buil t for

a part icular standard through speed -area tradeoffs. Altera also has the

NCO Compiler intel lectual property (IP) core that can generate a wide

range of architectures for oscil lators with spurious -free dynamic

range in excess of 115 dB and very high performance. Depending on

the number of frequency assignments to be supported, you can easily

instantiate the right number of digital up converters in a

programmable logic device (PLD).

2.3.3Crest Factor Reduction:

Wireless code-division multiple access (CDMA)-based systems

and multi -carrier systems such as orthogonal frequency division

multiplexing (OFDM) exhibi t signals with high crest factors (peak -to-

average ratios). Such signals drastically reduce the efficiency of PAs

used in the base stations. Altera FPGAs has a reconfigurable platform

for SDR base stations to implement CFR techniques that are

customized to each standard.

2.3.4 Digital Pre distortion:

The wireless standards and their high-speed mobile data

versions employ non-constant envelope modulation techniques such as

quadrature phase shift keying (QPSK) and quadrature amplitude


modulation (QAM). These places has str ingent l inearity requirements

on the power amplifiers. DPD linearization techniques, including both

look-up table (LUT) and polynomial approaches, can be efficiently

implemented using Stratix series FPGAs. The multipliers in the DSP

blocks can reach speed up to 480 MHz and can be effectively t ime -

shared to implement complex multiplications. Whe n used in SDR base

stations, we can implement Stratix series FPGAs to implement the

appropriate DPD algorithm that efficient ly laniaries the PA used for a

specific standard.

2.3.5 Digital Down converter:

On the receiver side, digital IF techniques can be used to sample an

IF signal and perform channelization and sample rate conversion in

the digital domain. Using under sampling techniques, high frequency,

IF signals ( typically 100+ MHz) can be quantified. For S DR

applications, since different standards have different chip/bit rates,

non-integer sample rate conversion is required to convert the number

of samples to an integer mult iple of the fundamental chip/bit rate of

any standard. Al tera’s DSP Builder tool has facil i ty of programmable

resample block that can perform non -integer decimation with

conversion ratios between 0.5 and 1


Figure 2.3. Digital Down converter3




2.3.5 Baseband Processing:

Wireless standards are evolving leap and bound to support

higher data rates through the introduction of advanced baseband

processing techniques such as adaptive modulation and coding, space -

time coding (STC), beam forming, and multiple -input mult iple-output

(MIMO) antenna techniques. The baseband signal processing devices

require enormous processing bandwidth to support such

computationally intensive algor ithms. Altera FPGAs has solution for

such applications with examples being channel coding for HSDPA and

beam forming.

The baseband components has to be flexible enough to enable

SDR functionali ty that is required to support migration between

enhanced versions of the same standard as well as the capabil i ty to

support a completely different standard. The remote upgradeabil i ty

feature using the Nios II based embedded processor, along with the

availabil i ty of a wide array of IP cores make Altera FPGAs an ideal

choice to enable such SDR functionali ty in both transmit and receive

signal processing data paths. Figure 2.4 shows a scenario where

Altera FPGAs can be easily reconfigured to support the baseband

transmit functions for ei ther WCDMA/HSDPA or 802.16a standards

through available Mega Core®

functions and reference designs such as

the Reed-Solomon encoder and inverse fast Fourier transform (IFFT).


Figure 2.4. SDR baseband data path reconfiguration4




2.2.6 Co processing Features:

As shown in Figure 2.5 , SDR baseband processing requires both

processors and FPGAs, where the processor handles system control

and configuration functions while the FPGA implements the

computationally-intensive signal processing data path and control ,

minimizing the latency in the system. To by standards, the processor

can switch dynamically between major sections of software while the

FPGA can be completely reconfigured, as necessary, to implement the

data path for the particular standard.

Data

Control

Figure 2.5 Co-Processing Architecture for SDR5

Altera FPGA coprocessor interface with a wide range of DSP support

with general-purpose processors provide increased system

performance and lower system costs . Altera’s SOPC Builder, which

includes an extension of the MATLAB’s Simulink environment,

known as DSP Builder, is a robust tool to facil i tate coprocessor

programming and integration. With DSP Builder, we can assemble



Processor

FPGA / SDR

Co Processor


parameterized blocks representing a plethora of functions ranging

from mixes through fully parameterized FIR fi l ters. Once a dataflow

system has been captured in DSP Builder, i t can be exported for use

as a coprocessor in any processor -based system assembled by SOPC

Builder . Using SOPC Builder’s interactive menus, we are able to set

the parameters of the components they intend to use and then can

choose the optimal Avalon system interconnect to connect the

selected components. In addit ion, you can store function blocks

created using SOPC Builder for reuse in future designs, providing

addit ional t ime and cost benefits .


Fig 2.6 Typical SDR


2.4 OMNET++

OMNET++ is open source tool to study protocol s for wireless

network. We use MIXIM , a mixed simulator combining various

simulation frameworks developed for wireless and mobile simulations

in OMNET++. It provides detailed models and protocols, as well as a

supporting infrastructure.

Environment models : Defines relevant parts of the real world and

i t ’s reflect ion, such as obstacles and others which can hinder wireless

communication

.Connectivity and mobility Defines movement in nodes and objects

and their influence on other nodes in the network varies. The

simulator has to track these changes and provide an adequate

graphical representation to i t .

Reception and coll ision In wireless environment , movements of

objects and nodes have an influence on the reception of a message.

The reception handling take care of modeling a transmitted signal

changes on i ts way to the receivers, taking transmissions of other

senders into account .

Experiment support The experimentation support is necessary to

help the researcher and scholar in comparing the results with an ideal

state, help him to find a suitable template for his implementation and

support different evaluation methods.

Protocol l ibrary MiXiM has a r ich set of protocol l ibrary , which

enables researchers to compare or enhance their ideas with already

implemented ones.


I t provides these so lutions by aggregating the approaches of several

exist ing simulation frameworks into one viz. the mobil i ty support ,

connection management, and basic design structure is taken from the

Mobili ty Framework (MF). The radio propagation models and air

interface are taken from the Channel Simulator and the protocol

l ibrary is taken from the MAC(Medium Access Control) simulator , the

Posit i f Framework and from the Mobili ty Framework. From the

experience gathered usages of each of these simulators, MIXIM

introduces unique extensions l ike 3D object support , models generate

from walls and obstacles that can influence the mobili ty and the

attenuation of radio signals, different frequencies and transmission

media (radio waves, ultrasound), ful l duplex multi-channel support in

3D of t ime, space and frequency, enabling Orthogonal Frequency

Division Multiplexing (OFDM) and Multiple Input Multiple Output

(MIMO) simulations, and support for various MAC protocols. Apart

from that researcher can develop their own protocol stack or enhance

exist ing one

MIXIM supports the simulation of networks having 1000 Plus

nodes, i t ’ low memory consumption and modular structure a llows the

adaptation of the level in detail . A TCL/TK basedd graphical

configurat ion interface helps to choose the right modules, stack them

in layers, and assign values to their parameters.

2.4.1 Simulation modules:

To collect global parameter l ike dimension of network in 2 -D or

3-D environmental model is used. MIXIM uses objects to model the


environment used in simulat ion . Objects has influence on radio

wave propagation and the mobili ty of other objects and nodes . . The

Object Manager is responsible for managing objects, providing

services to the rest of the simulation including calculating which

objects interfere within a given l ine -of sight between two nodes.

The Connection Manager module take charge of dynamic al

management of connections between interfering nodes. Connection

Manager knows exact posit ion of al l nodes and can query object

posit ions from the Object Manager. In general , MiXi M supports

multiple connection managers, responsible for different freque ncy

ranges such as radio waves and ultra sound in different bands l ike

GSM, UNNI, ISM etc. . Which can be used for Cognitive Radio based

application simulation

Node modules:

In a network network, MAC physical layer are found which are

connected by OMNET++ gates .A pair of gates are used for

connecting two different layer. First pair for passing up and down

messages and control messages. Second pair is used to support control

communication. Message exchange system between connections in

NIC can be used to exchange control messages between layer. In

wireless system MAC and PHY are t ightly coupled and specific to

different communication system. MiXim supports flexible MAC PHY

system to support Cognitive Radio system.

MiXim supports different modules to simulate different aspects

or aggregation module of wireless system like mobili ty module


responsible for mobili ty of node and object and their effect there

after. The battery module responsible for energy system of a

part icular module. ARP module for mapping address from MAC to

network .

The uti l i ty module is derived Mobili ty Framework ’s blackboard

module. I t has two main tasks: First one to provides a interface for

collecting statist ical data of a simulation. I t col lects stat ist ical data

with minimal impact on the performance of the simulation and

supports f lexibil i ty for different analysis methods. Finally , the uti l i ty

module maintains parameters that need to be accessed by information

sharing module within a node .

2.4.2 Base framework and protocol l ibrary:

MIXIM is divided into two parts: the base framework and the

protocol l ibrary. First one the base framework provides functionali ty

essential to simulate any wireless system. It contains connection

management, mobili ty, and wireless channel modeling. The protocol

l ibrary complements the base framework with a r ich set of standard

protocols . Which contains mobili ty models , MAC protocols . MIXIM

has a base module for each module in OMNET++.

2.5 MiXiM BASE MODELS:

as we are aware that s imulating a wireless communication

systems requires a suitable abstraction of the environment, the radio

channels , and the physical layer. To accomplish this MIXIM provides

a modeling framework. In t he basic modeling approaches discusses ,

the assumptions behind these approaches, and implementation


relevant aspects such as model abstraction level and model support

for trading off accuracy and calculation complexity.

Environmental model:

Simulations of any wireless system are carried out on a l imited

area, 10m X 10m, on which nodes and objects are placed. Nodes are

wireless devices with their protocol stack and are modeled as

isotropic radiators not having any physical dimension. An object is

anything or everything with a physical dimension that resides in the

propagation environment and can possibly affect (attenuate) a

wireless s ignal. Both, objects and nodes may be mobile. Nodes may

even be combined with objects

MiXiM simulation system model mobili ty as continuous

process and level of accuracy of model. In i t accuracy and

computational complexity can be user defined. MiXiM provides user

defined mobili ty parameter . This also provides specific updates of

posit ion in specific interval as defined facil i tat ing better and faster

interpolat ion.

MIXIM provides the Object Manager acts as a central authority

for managing objects in the wireless environment. Objects are

characterized by posit ion, dimensions, angle of rotation (optionally),

and frequency-dependent attenuation factors in 3-D. An object can

obstructs the l ine-of-sight between any pair of interconnected nodes

causes addit ional signal losses during transmission Since enti t ies can

be mobile, intersections of the l ine -of-sight of two nodes with one or

more objects must be de termined dynamically at runtime . For any


intersection with an object , i ts frequency -dependent attenuation factor

is sumed up to yield the addit ional at tenuation caused by the objects .

Connection modeling:

Connectivity modeling is a challenging task in wi reless s imulations.

In wireless system the “channel” between two nodes is the air or

vacuum, which is a broadcast medium and i t is difficulty to model as

one connection. MIXIM has a solution by dividing the modeling into

two parts. The first one is the wireless channel and i ts at tenuation

property. The second one is the connectivity between nodes .

A signal sent out by one node affects al l other nodes in the

environment. However, the signal is at tenuated, so that the received

power at nodes may vary and node very far away from the sending

node may receive very low signal that t is negligible . To reduce the

computational complexity in MIXIM, nodes are connected only when

they are within the range of maximal interference distance. The

maximal interference distance is a bound on the maximal distance up

to which a node possibly can disturb the communication of a

neighbor. A connection in MIXIM is probably better defined by i ts

complement: All nodes that are not connect, definitely they do not

interfere with each other. Following this concept, a node that wants to

receive a message from a communication peer, also receives al l

( interfering) signals and can, thus, decide on the interference level.

The presence of objects in the environment al so impacts the

maximal interference distance due skin effect . Objects may shield

two nodes from each other as shown in Figure2.7 because the


additional at tenuation that they imply reduces the maximal

interference distance.

Figure 2.7 3-D Channel Model6

Thus, objects may cause two nodes to be disconnected, increasing the

probabil i ty of the hidden node problem.

2.5.1 Wireless channel models:

Channel models in MiXiM express radio propagation effects as t ime

variant factors of the Signal -to-Noise Ratio (SNR) g of the received

signal . Although such SNR-based models represents abstract behavior

of the exact signal behavior, and, thus, adjusting the required

accuracy by selecting the modeled effects and t ime -scale. On this

SNR-level , MIXIM already includes the following widely accepted

channel models for path-loss, shadowing, large and small -scale fading

as defined in i t .

6 A.Kopke Etl . omnet++ workshop ’08


Physical layer models:

Physical layer implements modulation and Forward Error

Correction (FEC) coding and decoding functions define the bit error

rate and throughput of a system. The effect of these functions can be

modeled at SNR-level for wireless system.

FEC introduces a so-called coding gain at the receiver, which

can be expressed by a factor g to the SNR of the detected signal. This

coding gain depends on the used code, i ts rate Rc, and the employed

decoding algorithm . An encoded transmission has characterist ic of

g = 1, typical channel codes provide coding gains larger than 2 . This

SNR value compared to an SNR threshold in modeling transmission

errors in the decider module and a transmission error is assumed at

the receiver if g < thg . Typically, the SNR threshold thg calibrates

the system to stay below a given Packet Error Rate (PER) bound . I t is

selected well in advance depending on the receiver sensit ivity for the

chosen modulation scheme as per transceiver data shee t or

approximated. Selecting thresholds and coding gain independently per

terminal can model terminals employing different PHY parameters .

Furthermore, varying thresholds and coding gain over t ime support

rate adaptation .

SNR-based model easily extends to may type of receivers where

several channels are joined before the bit detection is made. Such

systems exploit differently faded channels and employ a fi l ter , l ike

Maximum Ratio Combining (MRC) to combine the signals received


from L channels to a single signal used for bit detection This

combining model can be used to model diversity receivers combining

signals in different dimensions, e.g. OFDM subcarriers, or multi -

antenna systems.

2.5.2 Connection management

The Connection Manager module is responsible for establishing

connections between nodes that are within the range of maximal

interference distance of each other and tearing down these

connections once they not in range. The loss of connectivity can be

crashed node or due to mobil i ty ( i .e. the nodes move too far apart) or

due to a change in t ransmission power etc.

An important factor influencing the maximal interference distance to

objects within the l ine -of-sight of two nodes as shown in Figure cause

the attenuation. As we know that , each object has a frequency

dependent attenuation factor. All objects have to register with the

central authority for managing objects in the simulation (Object

Manager). The object manager implements a l ine segment intersection

method that checks whether a l ine connecting two points in the

propagation environment intersects with the borders of one or more

objects. The addit ional at tenuat ion is then determined by summing up

the frequency dependent attenuation factors of the objects intersecting

the l ine. The connection manager uses this value for adjusting the

maximal interference distance of two nodes. MIXIM supports multiple


frequency ranges by means of mult iple connect ion managers ,

supporting Cognitive Radio Network .

As we know that , i t is possible to have multiple connection

managers in MIXIM. This enables the simulation of different

orthogonal spectrum ranges without compromising with performace in

term of memory consumption and computational complexity. I t is the

responsibil i ty of the NIC (and not the node) to register with the

desired connection manager. The respective connection managers wil l

connect only registered NICs .

Physical layer:

Physical layer is the central part of a node in MIXIM. I t is

responsible for sending and receiving messages, bit error calculation ,

and coll is ion detect ion . I t is also responsible for applying the channel

models used in the environment. Physical layer is divided into three

parts . The Base- PHY-Layer provides the interfaces to the MAC layer

and the physical layers of other communicating nodes . The Analogue

Models simulates the attenuation (l ike shadowing, fading and path

loss) of a received signal. The Decider is responsible for evaluation

of received signal (classification as noise or signal) and

demodulat ion (bit error calculation) of the received signal . To provide

a clear interface and to avoid memory overhead the analogue models

and the decider are implemented as pure C++ classes instead of

separate OMNET++ modules.


The signal concept:

The environment i t travels through influences the signal

strength of a message sent from one node to another . I t is modeled

with attenuation factors caused by shadowing, path loss and fading. A

message can be sent using multiple frequencies (e.g. OFDM) and

using multiple antennas (MIMO). Adding up all those possibil i t ies, a

message can have varying, at tenuation , sending power and bit -rate

(modeling modulation and coding) in 3-D of t ime, space and

frequency. MIXIM has a signal class to model this complex process.

Each message has to attach i t self with a signal object representing,

at tenuation, sending power and bit -rate in the 3-D of t ime, frequency,

and space. An example for the sending power (TX) is shown in Figure

2.8. To send a message, a node has to specify the sending power and

bit-rate in the appropriate dimensions. The receiving node then adds

the attenuation. On the basis of whole signal , bit errors can be

calculated.

BasePhyLayer:

Apart from message sending and receiving, the Base PHY Layer

acts as an interface between Air Frames , the Analogue Model and the

Decider . For better flexibil i ty and modulari ty, different analogue

models and deciders can be used with the physical layer. After

receiving a message, the physical layer first passes the message to the

analogue model, which calculates the attenuation part of the signal.

The physical layer is responsible for simulating the propagation and

transmission delay of the message.


Figure 2.8 Signal for sending power (TX)7

The message is passed at least twice to the decider: at the start of

message and at the end of the message. The decider can also request

to get the message at arbitrary t imes in between. After the decider

calculates the bit errors, the message has to be handed to the MAC

layer.

7 A.Kopke Etl . omnet++ workshop ’08


The physical layer stores all messages in to a class called the

Channel Info class. The Channel Info class act as service provider

that keeps track of all Air Frames on the channel. Channel Info

provides a function that returns all Air Frames intersecting with a pre

determined t ime interval. The decider uses this function in order to

calculate the SNR of a given signal .

Analogue models:

The receiving power of a received message is a given by

function f : Rn R from 3-D of t ime, frequency and space to

receiving power. MIXIM has to simulate features l ike path loss,

shadowing and fading.

Each of these attenuation sources can be represented by another

function a i : Rn R from 3-D of t ime, frequency and space to

attenuation. The attenuation of a signal is calculated by

implementations of shadowing, fading and path-loss models. Any

arbitrary number of analogue model s can be plugged into the physical

layer. Each analogue model is basically a fi l ter class for signals.

Summed attenuation of all analogue models g ives the

attenuation part of al l signal, which is calculated at the start of the

reception of a message. Together with the sending power of a

received packet the decider can later on calculate the SNR and bit

errors.

Decider:

The Decider has three main tasks to do . First one , the decider

has to classify and decided on incoming messages into receivable


messages or noise. Second one , at the end of receiving a receivable

message, the decider has to calculate the BER for the message. At last

i t has to provide information about the curren t state of the channel .

There are several models for determining how and when a

physical layer decides whether a message can be received or is just

noise. The decider in MiXiM supports al l of these models. After

arrival of a message, the physical layer pa sses the message to the

decider module. The decider can decide right away whether to treat

the message as noise or not, or i t can request the physical layer to

resubmit the packet after a certain t ime. This concept even enables

the decider to revise i ts decision (e.g. if a second, much stronger

message arrived in the meantime).

The maximum time that the decider can reques t the message

from the physical layer is at the end of the receiving process of the

message. This is also the t ime when the decider has to calculate the

BER for the message. In order to do so, i t requests al l intersecting

messages from the Channel Info in order to calculate the SNR for the

received message. I t then can either make a simple binary decision

(received correctly or not) or i t can calculate BER and posit ions,

depending on the complexity of the particular decider model.

The last task of the decider is to provide information about the

channel s tate. This channel st ate is needed at the MAC layer. The

MAC layer can request the decider to sense the channel for a certain

amount of t ime. The decider then returns state of the channel.


2.6 MiXiM PROTOCOL LIBRARY:

MIXIM allows every module in the simulation to be replaced by

another module, adding or overriding functionali ty to the base

implementation. For some of these modules there is already a wide

choice of implemented protocols available.

2.6.1 MAC protocols:

A Medium Access Control (MAC) protocol is designed to take

decisions on the sharing of a medium for communication between

nodes. In wireless systems, that shared medium is the air . A MAC

protocol needs to conclude when a node should send out messages,

such that the messages do not interfere with messages of other nodes.

MIXIM provides a wide variety of different MAC protocols

encompassing a significant proportion of the current design space for

MACs from 802.11 to 802.16 .

2.6.2 Network layer protocols:

MIXIM supports different networking protocols for a wide

variety of traffic paradigms (source -to-sink; any-to-any; local

neighborhood; etc), and these are further supported by the other

simulation modules, protocols. MIXIM is currently being used to tes t

the Ley Line Routing protocol .


Mobility models

MIXIM has a r ich l ibrary of mobili ty modules implemented,

which includes simple modules l ike “constant speed mobili ty” and

“circle mobili ty”, but also modules that parse ANSim trace fi les and

Bonn Motion fi les . I t is also support custom and user defined

mobili ty modules, by sub-classing from the Base Mobili ty class. The

Base Mobili ty class provides all the functionali ty needed for mobili ty

handling in MIXIM only the specific mobili ty pattern has to be

implemented in order to create a new mobili ty module.

2.7 Conclusions:

In early days network are analyzed on physically developed

tested, but due to high cost and scarcity of resource i t could not

widespread. Now a days due to advent of high end ICT technique i t is

possible to have virtual labs with support of real t ime remot e access

to ICT enable research equipment or emulator, simulator based

research . In same line research on protocol development for

cognitive radio networks were carried out with SDR and OMNET++

simulation tools .In which OMNET++ has rich set of wireless l ibrary

with support of MIXed Simulator (MiXiM) . MiXiM has support for

modeling 2D as well as 3D networks . I t also has support for TDM to

CDMA access mechanism. Physical modulation l ike PSK to OFDM

are also supported by the simulator . Through full f eature development

platform l ike OMNET++ gives near l ike simulation environment for

providing 3D wave propagation. The simulation setup include specific


feature for Indian climatic conditions. SDR are also used to gain some

inside story on reconfigurable r adio. The SDR also gives first hand

idea of various waveform and physical activity of CRN(Cognitive

Radio Network).

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