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Cognitive Radio Cognitive Network Simulator(NS2 Based)

The Cognitive Wireless Sensor Network simulator 31 is based on Castalia 32, and OMNET 33. The main advantage of this kind of simulator is that the physical and MAC layers are realistic. The authors added explicitly the difference between primary users (PUs) and SUs. In Figure 5.5 the Castalia cognitive radio module is shown. Alternatives to AKMA Network Simulator for Windows, Mac, Linux, FreeBSD, Software as a Service (SaaS) and more. Filter by license to discover only free or Open Source alternatives. This list contains a total of apps similar to AKMA Network Simulator. List updated: 8:11:00 AM.


Table of Contents:



1.3WHY BASED on NS2?

OPNET Network simulator is a tool to simulate the behavior and performance of any type of network. The main difference Opnet Network Simulator comparing to other simulators lies in its power and versatility. IT Guru provides pre-built models of protocols and devices. It allows you to create and simulation different network topologies. The Imunes-network simulator is one of the best alternatives to live experimental networks. The network simulation tool aims at realistic network topology framework. A network simulation software open source is based on FreeBSD and Linux operating system. Looks like you're using an older browser. To get the best experience, please upgrade. UPGRADE MY BROWSER.


2.1Design OVERVIEWfor CRCN

2.2CR routing

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3.1SOFTWARE and Installation

3.2Exemplary Demonstrations




4.3Cognitive Radio Research Groups

1.1Background of Cognitive Radio

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Cognitive radio network is a new emerging research area recently. It enhances the existing software-defined radio [1], whose physical layer behavior is largely defined in software. Cognitive radio has the following characteristics [2]. First, it is aware of its environment and its capabilities. Second, it is able to independently alter its physical layer behavior based on its previous experience and its current environment. Finally, it is capable of performing the complex adaptation strategies according to the cognitive cycle shown in [3]. With these capabilities, when spectrum environment changes around cognitive user, it is capable of sensing these changes and independently changing its physical layer settings such as transmission power, channel selection and etc to meet some constraints or QoS requirements of the users.

Cognitive radio gains popularity in the research area because it enables the current fixed spectrum channel assigned by FCC to be utilized by the new users. For example, most of the spectrums assigned to TV channels are idle most of the time, while wireless network users share a small range of spectrum, 2.4 G Hz and 5G Hz. When there are many wireless users at a time, the network is congested because of the limited channel. With the spectrum opportunities [4] provided by the cognitive radio network, the wireless network users are able to share the idle spectrum for TV channel, on the condition that it does not interfere with the normal TV channel.


As cognitive radio research is emerging, more and more researchers are looking forward to a simulator that is suitable for cognitive radio. However, there is no existing simulator that is suitable for the demand of cognitive radio simulations.Many researchers implemented their algorithms for cognitive radios on existing network simulator such as NS-2 [5], OPNET [8], QUALNET [11]. However, since these simulators are created for the ordinary wireless network, researchers can not easily implement their cognitive radio algorithms over those simulators. Hence, there is a demand to extend existing simulators to support cognitive radio simulators.We make use of existing NS-2 to extend it to support cognitive radio network simulation.

1.3Why based on NS-2?

There are several reasons to base on NS-2 for the development of cognitive radio simulators. First, NS-2 is open source software. Any contributions to NS-2 are accessible by people around the world. Second, NS-2 provides an interface for users to configure different network protocol at each network layers, which is essential for simulation. Third, NS-2 already provides many radio models, such as 802.11, 802.16, 802.15.3, 802.15.4. Users can make use of these radio models for cognitive radio network simulations. Finally, NS-2 has incorporated with different topology and traffic generators, which enable users to create different simulation scenarios.

1.4CRCN Simulator Overview

This cognitive radio cognitive network (CRCN) simulator is a software based network simulator for network-level simulations. It is based on open-source NS-2 (network simulator 2). CRCN simulator supports performance evaluations for the proposed dynamic spectrum resource allocation, power control algorithms, and the adaptive Cognitive Radio (CR) networking protocols including the CR MAC and the CR Routing protocols. 9general translation practicesindarin lessons. This simulator uses NS-2 to generate realistic traffic and topology patterns. For each node in this simulator, a reconfigurable multi-radio multi-channel PHY layer is available by customizing the spectrum parameters such as transmission power, propagation and etc

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The architecture block diagram for this simulator is illustrated in Figure 1. CRCN simulator enables the interface parameters transmission between different layers, as shown in arrows with blue color. Users just need to replace their own Routing and MAC algorithms according to NS-2 protocol design requirements with the existing one in the CRCN.