论文标题
突发模式通信系统中基于ELM的帧同步，具有非线性失真
ELM-based Frame Synchronization in Burst-Mode Communication Systems with Nonlinear Distortion
论文作者
论文摘要
在爆发模式通信系统中，接收器的帧同步（FS）的质量显着影响整体系统性能。为了确保FS，提出了一种基于极端学习机（ELM）的同步方法来克服非线性设备或块引起的非线性失真。在提出的方法中，首先进行预处理以通过使用经验知识来捕获同步度量（SM）的粗糙特征。然后，使用基于ELM的FS网络来减少系统的非线性失真并改善SMS。实验结果表明，与现有方法相比，我们的方法可以显着降低FS的误差概率，同时在鲁棒性和概括方面提高性能。
In burst-mode communication systems, the quality of frame synchronization (FS) at receivers significantly impacts the overall system performance. To guarantee FS, an extreme learning machine (ELM)-based synchronization method is proposed to overcome the nonlinear distortion caused by nonlinear devices or blocks. In the proposed method, a preprocessing is first performed to capture the coarse features of synchronization metric (SM) by using empirical knowledge. Then, an ELM-based FS network is employed to reduce system's nonlinear distortion and improve SMs. Experimental results indicate that, compared with existing methods, our approach could significantly reduce the error probability of FS while improve the performance in terms of robustness and generalization.
