Research On DSP Algorithm And Simulation In Optical Coherent Detection

Coherent detection can detect all the information encoded in the optical signal, which allows information symbols to be encoded in all the degrees of freedom available in a fiber, leading to improved power and spectral efficiency. Because of the business requirements of high-definition television and video conferencing, the capacity of network grows rapidly recently, which leads to the fact that the existed bandwidth cannot meet the network’s need. As a result, coherent detection technology arouses strong interest of researchers because of its high spectral efficiency.At the same time, the realization of high-speed analog to digital converter (ADC) and very large scale integrated circuit (VLSI) enables the digital compensation of fiber impairments in the GHz speed. Thus, the digital-signal-processing (DSP) technology will bring coherent detection more advantages. After coherent detection, DSP algorithm can compensate linear effects of fiber lossless, such as chromatic dispersion and polarization mode dispersion. In addition, carrier synchronization can also be done by using DSP algorithms. For these reasons, many researchers begin the study of DSP algorithms after coherent detection.This paper first introduces the basics of the DSP-based coherent optical system, and then describes the DSP algorithms used in the current coherent optical communication systems. The DSP algorithms discussed in this paper mainly include dispersion compensation algorithm, polarization crosstalk solution algorithm, non-linear compensation algorithm, frequency estimation algorithm as well as phase estimation algorithm. However, most of these algorithms have the shortcoming of high complexity. Focusing on the problem of high complexity, the author has made improvements in frequency estimation algorithm and phase estimation algorithm. The conjugate M-th power algorithm uses complex multiplier to remove the phase modulation information in frequency estimation, which will bring high computational effort. Based on this shortcoming, the author proposed a low complexity M-th power algorithm, which uses look-up table device to remove the phase modulation information. Besides the same performance with the conjugate M-th power, the new algorithm does not require complex multipliers, thereby greatly reduces the computational effort. In addition, the author also made innovation in phase estimation. Blind phase search is one of the most accurate phase estimation algorithms, which first assumes all the possible phase noise values, and then chooses the nearest test phase based on the principle of the shortest Euclidean distance. In order to ensure its high accuracy, the blind phase search algorithm commonly uses symbol-by-symbol estimation and a large number of test phases, which will bring great complexity. Based on the slow-changing characteristic of phase noise, the author proposed a two-step method which combines coarse estimation and fine estimation, as well as the sliding block method. The modified algorithm reduces the number of test phases and the repeated computational times of each symbol, and therefore reduces the complexity of the original blind phase search algorithm. The simulation results show that the complexity can be reduced by 50% at the cost of a 11% reduction of laser linewidth tolerance.