长短期记忆神经网络（LSTM-NN）辅助编码算法测试数据

长短期记忆神经网络（LSTM-NN）辅助编码算法测试数据主要面向能耗受限下的低时延前向纠错编码（FEC）技术研究，基于高性能服务器，利用Matlab、OptiStstem等软件产生，主要记录了不同光信噪比条件下OFDM子载波的信噪比分布、在极化码中采用固定设计与非固定设计的误帧率与误码率对比数据等仿真结果值，数据量17KB。This test dataset for coding algorithms assisted by Long Short-Term Memory Neural Network (LSTM-NN) is primarily intended for research on low-latency Forward Error Correction (FEC) technologies under energy consumption constraints. Generated on high-performance servers using software tools including Matlab and OptiStstem, the dataset mainly records simulation results such as the signal-to-noise ratio (SNR) distribution of Orthogonal Frequency Division Multiplexing (OFDM) subcarriers under various optical signal-to-noise ratio (OSNR) conditions, as well as comparative data of Frame Error Rate (FER) and Bit Error Rate (BER) between fixed-design and non-fixed-design schemes for polar codes. The total size of the dataset is 17 KB.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于能耗受限环境下的低时延前向纠错编码技术研究，通过高性能服务器利用Matlab和OptiStstem等工具生成仿真数据。它记录了不同光信噪比条件下OFDM子载波的信噪比分布，并对比了极化码中固定与非固定设计的误帧率和误码率，数据量约为17KB。