计算机科学
编码(社会科学)
接头(建筑物)
通信卫星
频道(广播)
卫星
传输(电信)
带宽(计算)
信道编码
数据传输
地球观测
多光谱图像
网络数据包
实时计算
遥感
计算机网络
电信
解码方法
人工智能
地质学
工程类
航空航天工程
数学
建筑工程
统计
作者
Olga Kondrateva,Stefan Dietzel,Björn Scheuermann
标识
DOI:10.1109/lcn58197.2023.10223379
摘要
Small satellites are widely used today as cost effective means to perform Earth observation and other tasks that generate large amounts of high-dimensional data, such as multispectral imagery. These satellites typically operate in low earth orbit, which poses significant challenges for data transmission due to short contact times with ground stations, low bandwidth, and high packet loss probabilities. In this paper, we introduce JSCC-SAT, which applies joint source-and-channel coding using neural networks to provide efficient and robust transmission of compressed image data for satellite applications. We evaluate our mechanism against traditional transmission schemes with separate source and channel coding and demonstrate that it outperforms the existing approaches when applied to Earth observation data of the Sentinel-2 mission.
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