# ELM-based Frame Synchronization in Burst-Mode Communication Systems with Nonlinear Distortion

arXiv: https://arxiv.org/abs/2002.07599 · HTML: https://mlsanity.com/paper/2002.07599/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Feb 2020.

## Built on by (most cited first, 1 of 1)

- [Deep Learning for 1-Bit Compressed Sensing-based Superimposed CSI Feedback](https://mlsanity.com/paper/2203.06606/) (2022)

## Abstract (arXiv)

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.