基于自编码器的多脉冲位置调制实现

Realization of multi-pulse position modulation based on autoencoder

针对应用于可见光通信的多脉冲位置调制(MPPM)方式的性能优化问题,提出了一种基于自编码器模型的MPPM传输设计方案。该方案分别利用全连接网络(DNN)和卷积神经网络(CNN)搭建自编码器模型,编码器端通过采用多阶段训练策略和自定义损失函数调控,实现了MPPM信源符号的生成;解码器端通过全连接层或一维卷积层构建的网络完成信道和MPPM信号特征学习等功能。仿真结果表明:基于自编码器的MPPM传输系统的误码性能可以达到且略优于传统最大似然序列检测性能。

Aiming at the performance optimization problem of multi-pulse position modulation(MPPM) method applied to visible light communication,an MPPM transmission design scheme based on autoencoder model is proposed.The scheme uses fully connected network(DNN) and convolutional neural network(CNN) to build autoencoder models respectively.The encoder side realizes the generation of MPPM source symbols by adopting multi-stage training strategy and self-defined loss function regulation,the decoding end completes the functions of channel and MPPM signal feature learning through a network constructed by a fully connected layer or a one-dimensional convolution layer.The simulation results show that the bit error performance of MPPM transmission system based on self encoder can reach and slightly better than the performance of traditional maximum likelihood sequence detection.