采用高斯噪声(GN)模型,研究了密集波分复用(DWDM)系统中不同调制格式的识别性能。调制格式共有23种,除包含MASK、MPSK和MQAM等规则调制格式外,也包含二维最优星座图、高阶APSK星座图等经过性能优化的调制格式。针对MASK、MQAM和MAPSK调制识别的部分特征参数随信噪比(SNR)变化的问题,提出了基于训练序列的阈值优化方法,使其低SNR下的识别率提高至93%以上。研究了DWDM系统的色散(CD)、非线性及传输距离对识别率的影响,仿真分析了不同调制格式的识别性能。仿真结果表明,MAPSK是最优的调制类型,识别率高于99%;二维最优星座图是次优的调制类型,其识别率高于93%。
This paper uses the Gaussian noise(GN)model to study the performance of the modulation recognition of different modulation formats for dense wavelength division multiplexing(DWDM)systems.There are twenty-three kinds of modulation formats studied in this work in total.Besides the common modulation formats,such as M-ary amplitude shift keying(MASK),M-ary phase shift keying(MPSK)and M-ary quadrature amplitude modulation(MQAM),2-dimensional optimal constellation and higher-order amplitude phase shift keying(APSK)constellation with optimized performance are also included in this study.In view of the situation that some feature parameters of MASK,MQAM and MAPSK are not constant if the signal-to-noise-ratio(SNR)changes,this paper proposes a method which uses the training sequence to find the threshold.The simulation results show that this threshold optimization method improves the probability of correct classification(Pcc)up to 93% for the region with the lowSNR.Finally,this paper obtains the Pccof the 23 modulation formats for the DWDM systems with various system parameters,such as the dispersion,nonlinearity and system total transmission distance.The modulation recognition performance of different modulation formats are analyzed through simulation.The simulation results show that MAPSK is the optimal format with Pccabove 99%,and 2-dimensional optimal constellation is the suboptimal one,with Pccabove 93%.