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Research of Cognitive Radio Spectrum Sharing Based on Evoluationary Algorithms

Author: PengZhen
Tutor: ZhaoZhiJin
School: Hangzhou University of Electronic Science and Technology
Course: Signal and Information Processing
Keywords: cognitive radio spectrum sharing color sensitive graph coloring quantum genetic algorithm particle swarm optimization algorithm shuffled frog leaping algorithm constrained optimization problem
CLC: TN92
Type: Master's thesis
Year: 2009
Downloads: 144
Quote: 3
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Abstract

Spectrum is a valuable nature resource which is becoming increasingly shortage with the rapid development of wireless communication technology and the people’s growing demand for broadband wireless applications. Cognitive radio technology is regarded as an intelligent wireless technology which can alleviate the scarcity and improve the fairly of spectrum utilization. This paper focus on one of the key technologies of cognitive radio, dynamic spectrum sharing, which allows secondary users using spectrum sensing technology to obtain available spectrum information and improves the spectrum utilization without interfering with the primary users’communication.First, the key technologies of cognitive radio and the basic theories and methods of a dynamic spectrum sharing are introduced.Secondly, based on the dynamic spectrum model, a coding method of feasible solution is proposed. Then the spectrum sharing algorithms based on evolutionary theories, i.e., quantum genetic algorithm, particle swarm optimization, and shuffled frog leaping algorithm are proposed. Simulation results show that the proposed algorithms are better than the color sensitive graph coloring based spectrum sharing algorithm.Next, the OFDM based cognitive radio sub-carriers and power allocation algorithm is studied. The spectrum sharing with quality of service requirement and power constraint on cognitive users is studied. The objective is to maximize the system throughput. This paper simplifies the mathematical model of the spectrum sharing problem by introducing new variables and proposes the joint power control and spectrum allocation algorithm based on particle swarm optimization. Using the penalty function which not only depends on the number of constraint violations but also on the degree of constraint violations, the multi-constrained nonlinear optimization problem is solved. In addition, the objective function and the violations of constraint functions may be in different scales, so the objective function and constraint functions are normalized. Simulation results show that the proposed method can achieve higher system throughput and improve the fairly of spectrum utilization under the constraints of transmit power and quality of service requirement.At last, the cross-layer optimization of cognitive radio is studied. This paper proposes a structure of cross-layer optimization and a cross-layer optimization algorithm based on co-evolutionary particle swarm optimization, which combines dynamic spectrum allocation and parameters cross-layer optimization. Simulation results show that the cross-layer optimization algorithm can not only allocate the spectrum dynamically according to the dynamic characteristic of the spectrum, but also have better performance than the hierarchical optimization.

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