光学学报, 2018, 38 (11): 1101002, 网络出版: 2019-05-09  

四进制自由空间激光通信信号的支持向量机检测算法 下载: 780次

Detection Algorithm of Support Vector Machine for Four-Level Free-Space Laser Communication Signals
作者单位
浙江大学现代光学仪器国家重点实验室光及电磁波研究中心, 浙江 杭州 310058
摘要
基于支持向量机(SVM)的机器学习方法提出了空间激光通信四进制脉冲振幅调制(PAM-4)信号的检测算法。利用功率谱密度反演方法仿真大气相位屏,结合Taylor冰冻流假设,得到了激光载波经过大气湍流信道的光场信号,叠加接收端高斯白噪声后,采用SVM检测算法针对所得的PAM-4信号进行判决。SVM检测算法与大气信道无关。SVM检测算法对接收信号数据进行分组,对各组数据进行交叉验证并完成学习,并对参数进行调整。通过多次二分类确定各电平之间的最优超平面。最后,SVM作出信号判决。SVM检测算法得到的误码率低于双步盲检测法,在大气湍流较弱的情况下与最优边界检测法的结果相当,说明SVM检测算法具有良好的性能。
Abstract
A detection algorithm based on support vector machine (SVM) is proposed for four-level pulse amplitude modulation (PAM-4) signals in free-space laser communication. Using the power spectral density inversion method, we simulate the atmospheric phase screen. Under the assumption of Taylor frozen flow, we obtain the optical field signal of the laser carrier propagating through the atmospheric turbulent channel. After Gaussian white noises to the signal are added at the receiving end, the PAM-4 signal is judged by the SVM detection algorithm. SVM detection algorithm is independent on the atmospheric channel. Firstly, SVM detection algorithm groups the received signal data, trains the learning and adjusts the parameters through cross validation of each packet data. Secondly, the optimal hyper-planes between every two adjacent levels can be determined by the cascaded two-level classifications. Lastly, the signal judgment can be made by SVM. The bit error rate (BER) obtained by SVM detection algorithm is better than that of the double-step blind detection, which is comparable to that of the optimal bound detection for weak atmospheric turbulences. It is shown that the SVM detection algorithm has a good performance.

何宏炜, 吴志航, 于召新, 冯湘莲, 江荷馨, 高士明. 四进制自由空间激光通信信号的支持向量机检测算法[J]. 光学学报, 2018, 38(11): 1101002. Hongwei He, Zhihang Wu, Zhaoxin Yu, Xianglian Feng, Hexin Jiang, Shiming Gao. Detection Algorithm of Support Vector Machine for Four-Level Free-Space Laser Communication Signals[J]. Acta Optica Sinica, 2018, 38(11): 1101002.

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