基于深度學(xué)習(xí)的低軌衛(wèi)星互聯(lián)網(wǎng)建設(shè)研究
打開(kāi)文本圖片集
摘要:為提升衛(wèi)星通信的效率和質(zhì)量,該文聚焦低軌衛(wèi)星互聯(lián)網(wǎng),運(yùn)用深度學(xué)習(xí)理論,創(chuàng)新性地提出一種低軌衛(wèi)星網(wǎng)絡(luò)算法。通過(guò)明確系統(tǒng)運(yùn)行問(wèn)題,構(gòu)建多智能體算法系統(tǒng),以優(yōu)化低軌衛(wèi)星互聯(lián)網(wǎng)建設(shè),滿足高質(zhì)量通信需求,為衛(wèi)星通信行業(yè)發(fā)展提供新思路與經(jīng)驗(yàn)借鑒。
關(guān)鍵詞:深度學(xué)習(xí);衛(wèi)星通信;低軌衛(wèi)星;互聯(lián)網(wǎng)建設(shè)
doi:10.3969/J.ISSN.1672-7274.2024.12.007
中圖分類號(hào):TN 927+.2;TP 393.4 文獻(xiàn)標(biāo)志碼:A 文章編碼:1672-7274(2024)12-00-03
Application Research on Low-Orbit Satellite Internet Construction Based on Deep Learning
GUO Xiangliang WEI Chuanqi ZHANG Shi
(1. China Academy of Information and Communications Technology, Beijing 100191, China;
2. Landspace Technology Corporation, Beijing 100176, China)
Abstract: To enhance the efficiency and quality of satellite communications, this paper focuses on low-orbit satellite internet and innovatively proposes a low-orbit satellite network algorithm using deep learning theory. By identifying system operational issues and constructing a multi-agent algorithm system, we aim to optimize the construction of low-orbit satellite internet to meet high-quality communication demands, providing new insights and experiences for the development of the satellite communication industry.
Keywords: deep learning; satellite communication; low-orbit satellite; Internet construction
0 引言
隨著物聯(lián)網(wǎng)技術(shù)的蓬勃發(fā)展,衛(wèi)星通信網(wǎng)絡(luò)中的用戶終端節(jié)點(diǎn)數(shù)量急劇增加,這一趨勢(shì)正有力推動(dòng)著衛(wèi)星通信行業(yè)的快速進(jìn)步。(剩余4182字)