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Study on the Searching and Tracking Algorithms for Polarization Mode Dispersion Compensation

Author: ZhangRongGuo
Tutor: ZhangXiaoGuang
School: Beijing University of Posts and Telecommunications
Course: Physical Electronics
Keywords: improved PSO algorithm cross tracing algorithm Polarization Mode Dispersion Compensation optical fiber communications
CLC: TN929.11
Type: Master's thesis
Year: 2010
Downloads: 27
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Abstract


In recent years, to meet the need of communication capacity, the bit rate of optical fiber communication is improving all the time. The polarization mode dispersion (PMD) which was not serious in low bit rate optical fiber communication becomes the main signal distortion factor for high bit rate optical fiber communication. As a result, we have to add the adaptive PMD compensator to the optical fiber communication systems.The most important part of the compensator is the control algorithm. Although the particle swarm optimization (PSO) algorithm is a comparatively good algorithm for PMD compensation, the convergent speed and success probability of the PSO algorithm make itself barely satisfactory, and need to be improved.The dithering-based particle swarm optimization (DPSO) algorithm and the gradient-based particle swarm optimization (GTPSO) algorithm which we will study in this thesis are two sorts of improved PSO algorithms.Also, we study an entirely new algorithm called cross tracing (CT) algorithm.They improve the global particle swarm optimization (GPSO) algorithm,as a result, they have advantage of fast convergent speed and success probability.The main task of this thesis is to test the performance of these three new algorithms via simulations and PMD compensation experiments.The work in this thesis is summarized as follows:The program code of the DPSO algorithm is given and its performance is tested via function simulation.The result reflects that this algorithm converges faster and will not be trapped into sub-optima.The program code of the GTPSO algorithm is given and its performance is tested via function simulation.The result reflects that this algorithm also converges faster and will not be trapped into sub-optima.The DOP map which we get from experiment is treated using the DPSO algorithm to test the efficiency of the algorithm. The result reflects that the DPSO algorithm is better than the GPSO algorithm. It converges faster and will not be trapped into sub-optima and is easier to find the optimum.The DOP map which we get from experiment is treated using the GTPSO algorithm to test the efficiency of the algorithm. The result reflects that the GTPSO algorithm is slower than the GPSO algorithm. But it also will not be trapped into sub-optima.The parameters of the GPSO, DPSO, and GTPSO algorithms are optimized in the PMD compensation experiments with various kinds of signals.The searching efficiency of the three algorithms is compared. The result shows that the DPSO algorithm is faster than the GPSO algorithm, and the GTPSO is slower than it.The parameters of the GPSO tracking algorithms are optimized in the PMD compensation experiments with various kinds of signals.After that, the tracking experiments are implemented and the tracking diagrams are depicted. The results show the tracking is very successful.The tracking efficiency of the GPSO, DPSO, and CT tracking algorithm is compared in the PMD compensation experiment with the CSRZ-DQPSK signal.The result shows the most efficient tracking algorithm is the CT algorithm.

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Wireless communications > Lightwave communications, laser communications > Optical fiber communication
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