摘要
通过采用正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)技术,实现了高速数据流的高效并行传输。通过自适应调制技术的动态调整能力,以响应信道状态信息(Channel State Information,CSI)的变化,从而在光纤传输中对抗色散和非线性效应等影响,优化系统性能。本研究提出基于深度神经网络(Deep Neural Networks,DNN)的自适应调制方案,通过实时监测子载波的有效信噪比(Signal to Interference plus Noise Ratio,SNR),动态调整比特分配和调制格式,以适应变化的信道条件。仿真结果表明,与固定调制格式相比,所提出的自适应调制方案在相同系统速率下显著降低了误码率,同时在不同误码率目标下均实现光信噪比的增益。
By using Orthogonal Frequency Division Multiplexing(OFDM)technology,efficient parallel transmission of high-speed data streams has been achieved.By utilizing the dynamic adjustment capability of adaptive modulation technology to respond to changes in Channel State Information(CSI),the system can resist dispersion and nonlinear effects in fiber optic transmission and optimize system performance.This study proposes an adaptive modulation scheme based on deep neural networks(DNN),which dynamically adjusts bit allocation and modulation format to adapt to changing channel conditions by monitoring the effective signal-to-noise ratio(SNR)of subcarriers in real-time.The simulation results show that compared with a fixed modulation format,the proposed adaptive modulation scheme significantly reduces the bit error rate at the same system rate,while achieving gain in optical signal-to-noise ratio at different bit error rate targets.
出处
《现代传输》
2024年第6期72-75,共4页
Modern Transmission
关键词
高速大容量
光通信系统
自适应调制
深度神经网络
High speed and large capacity
Optical communication system
Adaptive modulation
Deep neural networks
