Research On Polarization Demultiplexing Technology In Polarization Multiplexing System

With the growth of people's demand for communication services, enhancing system capacity is imperative. Using the polarization property of optics transmitted in a single mode fiber, Polarization multiplexing (PM) technique aims at creating two independent communication channels over the transmission wavelength by using the independent and mutually orthogonal polarization, which can double the capacity of optical fiber communication system and increase spectrum efficiency. This technique can upgrade system rapidly and economically on the existing optical network. The two polarizations can be affected by polarization mode dispersion, polarization dependent loss etc., which will cause crosstalk between each other. The most important problem to be solved in polarization multiplexing system is eliminating the crosstalk between the received signals, which can be called polarization de-multiplexing. According to the principle of polarization multiplexing technology and characteristics of polarization multiplexing system, the major work of this paper is studying and finding a suitable method for polarization de-multiplexing. This paper has done a lot of further work of polarization multiplexing technology on the basis of previous research. In order to verify the validity of polarization de-multiplexing algorithm, we establish the simulation model of polarization multiplexing system. First of all, we research on the polarization de-multiplexing method carried out by using constant modulus algorithm (CMA).The Recursive Least Squares constant modulus algorithm (RLS-CMA) is modified based on feature of transmission matrix in polarization multiplexing system, and then we show the de-multiplexing results of this algorithm. In order to get a more robust de-multiplexing algorithm based on the CMA, it is the first time to use RLS-CMA algorithm based on QR decomposition (QR-RLS-CMA) as the de-multiplexing algorithm in polarization multiplexing system. This algorithm is not sensitive about initial values, furthermore it has strong robustness. Moreover, we research on the polarization de-multiplexing method carried out by using independent component analysis (ICA). According to characteristics of polarization multiplexing system, a fixed-point algorithm based on complex maximization of negentropy is used as the de-multiplexing method in polarization multiplexing system for the first time. This algorithm can realize de-multiplexing of different modulation format just by adjusting nonlinear function. It doesn't need solving inverse of channel matrix, which can significantly reduce complexity while guaranteeing the de-multiplexing performance. The works in this paper are as follows:Firstly, a simulation model of the polarization multiplexing system based on the principle of polarization multiplexing technology has been established by using Optisystem 9.0 fiber communication software. The signal processing module requiring for de-multiplexing is realized by MATLAB programming. Each part of the system has been introduced in detail. The origins of polarization mode dispersion and polarization dependent loss have been analyzed; in addition, the causes of crosstalk have been researched. As the principle of polarization de-multiplexing has been analyzed from the theoretical, we get the conclusion that the essence of de-multiplexing is solving the separating matrix.Secondly, polarization de-multiplexing is carried out by using CMA. We focus on the Stochastic Gradient Descent constant modulus algorithm (SGD-CMA), RLS-CMA algorithm and QR-RLS-CMA algorithm, giving the mathematical deduction of these algorithms. The main steps and initial value of these algorithms have been given in table. The RLS-CMA algorithm is modified based on feature of transmission matrix in polarization multiplexing system, and QR-RLS-CMA algorithm used as the de-multiplexing method in polarization multiplexing system at the first time. De-multiplexing results of these algorithms have been analyzed by using constellations diagram and eye diagram, comparing the convergence among these algorithms, and then we get the conclusion that QR-RLS-CMA algorithm has the best performance among these algorithms.Thirdly, polarization de-multiplexing is carried out by using ICA. The basic conception of complex ICA and the estimation principle are introduced in detail, and then the feasibility of the de-multiplexing of polarization multiplexing system with complex ICA is analyzed. The fixed-point algorithm based on complex maximization of negentropy (T-CMN) is developed by MATLAB programming. The main steps of deflationary regularization T-CMN algorithm and symmetric regularization T-CMN algorithm are given in table, and then we show the de-multiplexing results of symmetric regularization T-CMN algorithm by simulation. The symmetric regularization T-CMN algorithm and tensor based ICA algorithm have been compared in several aspects, the results shows that symmetric regularization T-CMN algorithm doesn't need solving inverse of channel matrix, which can significantly reduce complexity while guaranteeing the de-multiplexing performance. Comparing de-multiplexing performance between CMA and T-CMN algorithm by using eye diagram, the result shows that T-CMN algorithm has better robustness.Finally, we use Viterbi-Viterbi algorithm to estimate signal phase to recover the original signal, and then we get the received bit sequence by using threshold judgment. System bit error ratio can be tested through bit error test module by comparing the bit sequence between transmitted bits and received bits. After measurement of bit error rate, the result shows that this system is error-free.