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Research on Reconfiguration Management in Cognitive Radio Network

Author: HeZuo
Tutor: ZhangPing; FengZhiYong
School: Beijing University of Posts and Telecommunications
Course: Communication and Information System
Keywords: cognitive wireless networks reconfiguration management artificial intelligence technology adaptive radio resource management handover network topology management
CLC: TN925
Type: PhD thesis
Year: 2013
Downloads: 0
Quote: 1
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With the development of mobile communications, there are three distinct trends in mobile communications system currently:Firstly, the growing number of mobile users cause data traffic having a continued risen; Secondly, the mobile users’requirements in quality of service and the type of application have further growth, meanwhile, the type and amount of multimedia services have explosive growth; The third is, due to the development of network standards, the coexistence of heterogeneous network is increasingly common. Heterogeneous network is different from the homogeneous network for it demanding a more powerful and intelligent management.With the application from the three trends demanding more and more spectrum resource, the available spectrum resource in wireless systems is gradually depleted. In this context, we need a more effective spectrum allocation scheme to improve the spectrum utilization. Meanwhile, faced to the complex situation in heterogeneous network, an effective integration scheme is also necessary. In this context, the concept of cognitive radio network, with its advantages in intelligent spectrum management and heterogeneous network fusion management, is proposed to solve some major issues above. Cognitive radio network shoulders such a complex mission, which means it has to understand users’ requirement, achieve the interoperability in heterogeneous networks, and adapt the dynamic environment, in order to advance the end-to-end performance. However, the series of operations are achieved by the cognitive reconfiguration technique. Cognitive reconfiguration technology has become an essential research area in cognitive wireless networks, for it can make reconfiguration decision intelligently and autonomously to meet user requirement, achieve interoperability among heterogeneous networks, make full use of wireless resource and adapt to the dynamic wireless environment, through adjusting the configuration of terminal device and network device.This paper studies the reconfiguration management and operation in cognitive radio network, and presents the architecture and implementation mechanism of the reconfiguration management in cognitive radio network, which achieve the research of cognitive reconfiguration management integrated.These detailed contents are presented in following sections:Firstly, the architecture of reconfiguration management plane in cognitive radio network is investigated. It starts from the functional analysis and the major functional modules designing. And then, a detailed analysis on reconfiguration implement and a functional architecture classification is proceeding, which is helped to give an overall reconfiguration management architecture model.Then, the objects which need to adjust in cognitive reconfiguration process are analyzed. The different objects are divided into two scales. The parameters reconfiguration and wireless resource reconfiguration are defined as small-scale reconfiguration, meanwhile, the work pattern reconfiguration and network topology reconfiguration are belong to large-scale category reconfiguration management.This paper presents the analysis on complex wireless environment parameters, which can draw to the impact of system performance from parameter changing. The relationship between the parameters and system performance can help to adjust correspondence system configuration when environment changes. This kind of adjustment can achieve the end-to-end system performance. In wireless resources reconfiguration aspect, we mainly research on the dynamic channel allocation problems: assign the idle channel to cognitive users and ensure the primary users from interference, so as to enhance the utilization of spectrum, and furthermore, to enhance the system performance. In this paper, the adaptive neural network inference system and ant colony algorithm are introduced in analyzing complex parameters. Artificial intelligence technology can significantly reduce the complexity in the calculation process.In work pattern reconfiguration scheme, the cognitive user terminal has capability of changing the operating mode so that they can switch among heterogeneous networks. Based on the requirement of cognitive user, reconfiguration management examines the performance from various heterogeneous networks, and then, initiates the switching behavior in the network to fulfill the user’s satisfaction.For the network topology reconfiguration, this paper presents some schemes such as network self-configuration, self-healing and self-management, to prove that the reconfiguration management can optimize the entire network. In this paper, the optimization objective includes the user requirement, link capacity and primary user protection. The topology reconfiguration algorithm helps network topology to adapt environment to cope with heterogeneous networks coexistent problem, network failure problem and hidden node problem.Finally, the conclusion summarizes the entire contents, and pointes out the direction of the future research.

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