基于条件GAN的无人机智能光通信

首先介绍了无人机激光通信技术的先进性和重要性,然后引入深度神经网络(DNN)来开发无线端到端通信系统,其中DNN被应用于:编码,解码,调制和均衡。准确的信道状态参数(CSI)是计算DNN所必须的,但在激光通信系统中,信道信息很难提前获得或随时间和环境变化很大,本文将使用条件生成对抗网(GAN)来表示信道效应,其中发射机的编码信号和与导频数据相对应的接收信号将用作条件信息。通过对加性高斯白噪声(AWGN)和对数正态信道的仿真结果表示,该方法可以做到无明确CSI情况下完成高质量传输。

Unmanned aerial vehicle intelligent optical communication based on condition GAN

This paper first introduces the advancement and importance of UAV laser communication technology,and then introduces Deep Neural Network (DNN) to develop wireless end-to-end communication systems,where DNN is applied to:encoding,decoding,modulation and equalization.Accurate channel state parameters (CSI) are necessary for computing DNN,but in laser communication systems,channel information is difficult to obtain in advance or varies greatly with time and environment.This paper will use conditional generation network (GAN) to represent channel.The effect,in which the coded signal of the transmitter and the received signal corresponding to the pilot data is used as condition information.The simulation results of additive white Gaussian noise (AWGN) and Lognormal channel show that the method can achieve high quality transmission without clear CSI.