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Research on Parameter Optimization and Sensitivity Analysis in Cognitive Radio Networks

Author: LiJunJian
Tutor: FengWenJiang
School: Chongqing University
Course: Circuits and Systems
Keywords: Cognitive radio Cognitive engine Parameter optimization Particle swarm optimization The sensitivity analysis
CLC: TN925
Type: Master's thesis
Year: 2011
Downloads: 68
Quote: 0
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Abstract


Cognitive radio is a spectrum reuse, effectively improve the spectrum utilization intelligent wireless communication technology, provides a new way to achieve dynamic spectrum sharing. Papers relying on the National Natural Science Foundation of China-based cognitive radio mesh network topology management, MAC mechanism and adaptive resource allocation strategy \Cognitive radio parameter optimization based on changes in the external environment, real-time access to current optimal operating parameters; parameter sensitivity analysis is to seek the intrinsic link between the transmission parameters and system performance goals. Parameter sensitivity analysis and parameter optimization combination can effectively guide the adaptive adjustment of the transmission parameters, but also targeted focus on the main factors, secondary factors are ignored, thereby reducing the complexity of the signal processing and computation. The research topics include: 1) starting from the basic principles and key technologies of cognitive radio, analyzes and compares the technical characteristics of the typical cognitive radio decision engine and cognitive engine model, the mathematical description of the multi-objective optimization and traditional multi-objective optimization methods. 2) cognitive radio adaptive according to environmental changes and user needs to adjust its operating parameters. Most of the existing cognitive engine genetic algorithm to optimize the parameters, but with the increase in the number of cognitive users, an increase in genetic algorithm chromosome, resulting algorithm converges for a long time, unable to meet the needs of real-time communication. Therefore, parameter optimization in cognitive radio, seek high search efficiency, fast convergence and high stability of the optimization algorithm is one of the cognitive radio. Particle swarm optimization based on cognitive radio transmission parameters, optimization objective, and its fitness function, the modified inertia factor particle swarm optimization to optimize the cognitive radio parameters and effectiveness of the algorithm is verified by simulation, search efficiency and convergence speed are superior to the genetic algorithm, algorithm stability meet the requirements of real-time processing of cognitive radio. 3) Parameter sensitivity analysis in order to obtain different transmission parameters on cognitive engine judgment and to quantify. Parameter sensitivity analysis and optimization process combines sensitivity analysis of cognitive radio transmission parameters, respectively, in different communication mode, selectively removed from the objective function less sensitive parameters to reduce the complexity of processing and handling delay.

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Wireless communications > Radio relay communications,microwave communications
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