Signal Detection in Satellite-Ground IoT Link Based on Blind Neural Network

被引:0
|
作者
Guan, Qing-yang [1 ,2 ]
Shuang, Wu [1 ]
机构
[1] Xian Int Univ, Coll Engn, Xian 710077, Peoples R China
[2] Shenyang Aerosp Univ, Coll Elect & Informat Engn, Shenyang 110136, Peoples R China
基金
中国国家自然科学基金;
关键词
MASSIVE MIMO;
D O I
10.1155/2021/5547989
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
At present, there are many problems in satellite-ground IoT link signal detection. Due to the complex characteristics of the satellite-ground IoT link, including Doppler and multipath effect, especially in scenarios related to military fields, it is difficult to use traditional method and traditional cooperative communication methods for link signal detection. Therefore, this paper proposes an efficient detection of satellite-ground IoT link based on the blind neural network (BNN). The BNN includes two network structures, the data feature network and the error update network. Through multiple iterations of the error update network, the weight of BNN for blind detection is optimized and the optimal elimination solution is obtained. Through establishing a satellite-to-ground link model simulation of the low-orbit satellite, the proposed BNN algorithm can obtain better bit error rate characteristics.
引用
收藏
页数:10
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