Cognitive Radio Network Simulator

Cognitive Radio Network Simulator

Overview of Cognitive Radio Network

         The cognitive radio network simulator is considered as the software based network simulator and that is deployed in the network level simulation. The cognitive radio technology is used for the efficiency of the utilization of wireless network spectrum. It is one of the most significant methods which are deployed to sort out the issues based on spectrum scarcity. The cognitive radio networks are considered as the spectrum resource utilization with the provision of extra communication capability.

Primary Usage of Cognitive Radio Network

           Before getting deep into cognitive radio network simulator, the research scholars have to get some knowledge about the fundamentals points and the uses within it. Thus, we have listed down the significant benefits in the cognitive radio network simulator for your ease.

  • It is supportive for the process of performance evaluation that is proposed for the power control algorithms, adaptive cognitive radio networking protocols and dynamic spectrum resource allocation for cognitive radio routing and cognitive radio protocols. In addition, the users have to utilize the process of radio models in cognitive radio network simulations as per the models such as
  • 15.4
  • 15.3
  • 15.16
  • 15.11
  • It is deployed for the investigation and evaluation of the impact of lower layers such as physical and MAC layers based on network and transport layers protocols. The significance of end to end delay, throughput as QoS requirements and packet drop probability in real time are reliable for the applications with the metrics that are evaluated through cognitive radio network

Topical Modules in Cognitive Radio Network Simulator

         Let us take a look into the notable modules with their functions which are considered as more important in the research process and it is helpful for the research scholars to elevate their research based on cognitive radio network simulator.

  • CR simulation network models
  • It is created through the utilization of INETMANET 2.0 and OMNeT++ 4.6 and adaptable for the modules that are created through CR network. The data transmission is simulated through the ping protocols and that is functioning through the adaptation process. The two tests are conducted for the validation of cognitive radio simulation network which is enhanced
  • The users can perform the cognitive radio network through the utilization of peculiar cognitive functions based on the generic device OSI stacks

Significant Plugins in Cognitive Radio Network Simulator

         Our research experts are providing significant knowledge about cognitive radio network simulator. In that way, this section is all about the plugins that are used in the research process of cognitive radio network simulator along with its characteristics in the following.

  • RFnest
  • Radio frequency network emulator simulator tool is abbreviated as RFnest and it is utilized for the creation of air environment through the alterations of channel properties through the digital process
  • It is utilized in place of the air transmissions
  • NEST
  • Network emulator simulator testbed is abbreviated as NEST and it is denoted as the provision of implementation based on plug and play cognitive network implementation with the software defined radios (SDRs)

Prominent Classes in Cognitive Radio Network Simulator

         Research scholars have to know about the required classes to implement the research project in cognitive radio network simulator. To make that ease, our research experts have enlisted the substantial libraries with its appropriate functions in the following.

  • SpectrumManager
  • Spectrum-manager.cc and spectrum-manager.h source files are deployed as the code for these classes in Ns3. It is deployed to control the spectrum process and it is similar to the processes such as
  • Spectrum module definition
  • Spectrum module definition
  • State initialization
  • PacketTypePacketTag
  • The cognitive-packet-tags.h and cognitive-packet-tags.cc source files are used as the code for these classes. The class is used to control the transmitted packets based on the cognitive networks. In addition, the classes are classified into various types and they are
  • Control packets
  • Data packets

Intergrated Tools in Cognitive Radio Network Simulator

         Hereby, we have highlighted the significant and integrated tools which are essential to develop a research project in cognitive radio network simulator.

  • OMNeT++ is integrated with the MiXim package
  • Ns2 is integrated with CogNs simulation framework in cognitive radio networks

Programming Languages in Cognitive Radio Network Simulator

          Below are fundamental programming languages used in cognitive radio network simulator, the research scholars can choose any programming language and it can get our comprehensive guidance for the research project implementation.

  • OMNeT++
  • .ned
  • Ns3
  • .h
  • .cc
  • Ns2
  • .otcl

OS Support in Cognitive Radio Network Simulator

         Basic operating system requirement for the implementation of cognitive radio network simulator based research projects are listed below. Research scholars can reach our technical expert for configuration support.

  • Ubuntu – 18.04
  • Windows – 10 (64 bit)

Tools Versions in Cognitive Radio Network Simulator

        Below, we have highlighted the tools versions based on the cognitive radio network simulator, similarly research scholars can select various tools and get complete details about that by reaching our research experts.

  • OMNeT++ 5.4.1
  • Ns – 2.28
  • Ns – 3.30.1

Substantial Protocols in Cognitive Radio Network Simulator

         The major protocols used in CRN are listed below for quick understanding but there are diverse protocols which can be implemented in cognitive radio network simulator based projects. We are here to assist the research scholars to dig out the best protocol for your project implementation.

  • DSR
  • DSDV
  • AODV
  • Ad hoc on demand distance vector

Essential Parameters in Cognitive Radio Network Simulator

         Here, we have enlisted the significant parameters that are used in the process of cognitive radio network simulator.

  • Reachability
  • It is defined as the capability to reach the destination that too in short distance and measured through the terms of kilometers and meters
  • Time
  • It is considered as the time required for simulation process in network and measured through minutes and seconds
  • Speed
  • It is denoted as the rate of data that is moved through the communication channels and it is measured over the bit per second
  • Distance
  • Distance among two nodes and the complete route for source node towards the destination node. It is measured through the kilometer and meter

Subject Based Modules in Cognitive Radio Network Simulator

          Researchers must be aware of each modules of cognitive radio network and we offer the complete support for research students to understand and implement each module under cognitive radio network simulator.  For quick reference, we have just listed two major modules used. Hereby, we have listed down the research subject areas with the appropriate tools in the cognitive radio network simulator.

  • crSimulator
  • It is the model based on cognitive radio ad hoc network simulations in OMNeT++
  • Ns3
  • It is deployed in the cognitive network for the performance such as
  • Spectrum allocation
  • Spectrum sensing

Key Syntax in Cognitive Radio Network Simulator

         Below, we have highlighted the list of significant composition of the research projects to check and allocate the channel based on tag based packet classification based on cognitive radio network simulator.

TypeId
PacketChannelPacketTag::GetTypeId (void)
{
static TypeId tid = TypeId
("ns3::PacketChannelPacketTag").SetParent
().AddConstructor () ;
return tid;
}
TypeId
PacketChannelPacketTag::GetInstanceTypeId (void) const
{
return GetTypeId ();
}
in ns3 source code for spectrum manager,
SpectrumManager::SpectrumManager(Ptr mac, Ptr phy, int id, Time sense_time, Time transmit_time) {
m_wifiMac=mac;
m_nodeId=id;
m_wifiPhy = phy;
m_isPuOn=false;
m_isSensing=false;
m_isSwitching = false;
// State Initialization
m_senseTime=sense_time;
m_transmitTime=transmit_time;
// Spectrum Module Definition
m_sensingMod=new
SpectrumSensing(this);
m_decisionMod=new SpectrumDecision(this);
// Setup sense and handoff ended callback at PHY
//m_wifiPhy->SetSenseEndedCallback(MakeCallback (&SpectrumManager::SenseEnded, this));
//m_wifiPhy->SetHandoffEndedCallback(MakeCallback(&SpectrumManager::HandoffEnded, this));
}
SpectrumManager::~SpectrumManager() {
}

Notable Applications in Cognitive Radio Network Simulator

            Some of the major applications which exploit cognitive radio network are listed below. In recent days, applications uses cognitive radio network simulators are in peak and we provide support for all type of applications and research ideas.

  • Medical body area networks
  • It is deployed as the omnipresent patient monitoring process and it is assistive in notifying process of doctors based on the virtual information about the patients and the data such as
  • Electrocardiogram
  • Blood oxygen
  • Blood pressure
  • Sugar level
  • Emergency and public safety communications
  • Dynamic spectrum access

Major Algorithms in Cognitive Radio Network Simulator

         Listed below are considered as some of the required algorithm used in recent cognitive radio network simulator based applications but our research experts offer support for all types of algorithms to provide efficient and desired results.

  • BW based algorithm
  • DR based algorithm
  • DDMAC algorithm

Trending Areas in Cognitive Radio Network Simulator

        We have listed most recent research areas here for research scholars to get a quick grasp over the subject cognitive radio network simulator. They can bring their research area and get our complete guidance from our research experts,

  • Radio configuration
  • It is deployed to produce the appropriate results based on cognitive radio network
  • Cognitive parameters
  • It is used to acquire the efficient spectrum process results

Required Metrics in Cognitive Radio Network Simulator

          Generally, the metrics are involved in the evaluation process of cognitive radio network simulator research projects. Here, we have listed down the notable metrics.

  • Routing overhead ratio
  • It is considered as the ratio among number of generated control packets and the total number of generator packets
  • Packet delivery ratio
  • It is ratio among number of data packets that are received and generated
  • End to end delay
  • It is latency time that is transmitted over packets through route from end to end

Significant Process in Cognitive Radio Network Simulator

         Let us discuss about the required process that are used to develop the spectrum sensing process in cognitive radio network simulator.

  • Interference temperature detection
  • Transmitter detection
  • Cycle stationary detection
  • Energy detection
  • Matched filter detection
  • Cooperative detection
  • Relay assisted spectrum sensing
  • Centralized spectrum sensing
  • Decentralized spectrum sensing

Key Steps in Cognitive Radio Network Simulator

          Our research professionals have listed down the step involved in the process of the wireless body area network in cognitive radio network simulator.

  • Functions
  • Mobility
  • Management
  • Sharing
  • Sensing
  • Techniques
  • Auctions
  • MAS
  • Markovian queuing model
  • Games theory
  • Objectives
  • Minimize
  • Consumption of energy
  • Interference
  • Maximize
  • Equality
  • Use of spectra
  • Transfer rate

Major Parameters in Cognitive Radio Network Simulator

         The substantial parameters which are utilized in the evaluation process of cognitive radio network simulator are highlighted in the following.

  • Spectrum opportunity
  • Estimated delay
  • Available resources
  • Packet loss rate
  • Transmission rate
  • Delay deadline
  • Packet length
  • Priority

Routing Protocols in Cognitive Radio Network Simulator

          Our research experts have listed down the significant routing process in the cognitive radio network simulator in the following.

  • STOD-RP
  • Spectrum tree based on demand routing protocol for multi hop cognitive radio networks
  • CTBR
  • Cognitive tree based routing
  • C-TRP
  • Tree routing protocol for cognitive radio network

Latest Project Titles in Cognitive Radio Network Simulator

          Let us take a look into the most recent project titles in the cognitive radio network simulator. We have highlighted these titles through analyzing various research papers from topical research journals based on cognitive radio network simulator.

Live Tasks
Technology Ph.D MS M.Tech
NS2 75 117 95
NS3 98 119 206
OMNET++ 103 95 87
OPNET 36 64 89
QULANET 30 76 60
MININET 71 62 74
MATLAB 96 185 180
LTESIM 38 32 16
COOJA SIMULATOR 35 67 28
CONTIKI OS 42 36 29
GNS3 35 89 14
NETSIM 35 11 21
EVE-NG 4 8 9
TRANS 9 5 4
PEERSIM 8 8 12
GLOMOSIM 6 10 6
RTOOL 13 15 8
KATHARA SHADOW 9 8 9
VNX and VNUML 8 7 8
WISTAR 9 9 8
CNET 6 8 4
ESCAPE 8 7 9
NETMIRAGE 7 11 7
BOSON NETSIM 6 8 9
VIRL 9 9 8
CISCO PACKET TRACER 7 7 10
SWAN 9 19 5
JAVASIM 40 68 69
SSFNET 7 9 8
TOSSIM 5 7 4
PSIM 7 8 6
PETRI NET 4 6 4
ONESIM 5 10 5
OPTISYSTEM 32 64 24
DIVERT 4 9 8
TINY OS 19 27 17
TRANS 7 8 6
OPENPANA 8 9 9
SECURE CRT 7 8 7
EXTENDSIM 6 7 5
CONSELF 7 19 6
ARENA 5 12 9
VENSIM 8 10 7
MARIONNET 5 7 9
NETKIT 6 8 7
GEOIP 9 17 8
REAL 7 5 5
NEST 5 10 9
PTOLEMY 7 8 4

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