Researching | Satellite Internet of Things Load Estimation and Prediction

Study On Optical Communications, Volume. 50, Issue 5, 23001301(2024)

Satellite Internet of Things Load Estimation and Prediction

Xiwen MAO, Haitao WANG^*, and Gengxin ZHANG

Author Affiliations

School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China

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Figures&Tables (8)

References (14)

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Figures & Tables(8)

Fig. 1. IoT model of low orbit satellite

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Fig. 2. Load estimation and prediction process

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Fig. 3. The simulation diagram of the load estimation

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Fig. 4. The storage structure of the single LSTM cell

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Fig. 5. The flow chart of the load prediction

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Fig. 6. The simulation graph of the load prediction

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Table 1. Simulation parameters

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Table 1. Simulation parameters

服务时隙/个	终端数量/个	业务到达模型	概率分布函数	可用前导码数/个	退避算法	退避最大窗口值	前导码选择方式
17 000	70 000	服从Beta分布	60t²(T－t)³/T⁶	32	二进制随机退避	32个时隙	随机选择

Table 2. LSTM model parameters
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Table 2. LSTM model parameters
第1层神经元个数第2层神经元个数最大迭代次数初始学习率优化器损失函数神经元损失概率
128 64 1 000 0.002 Adam MSE 0.2

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Xiwen MAO, Haitao WANG, Gengxin ZHANG. Satellite Internet of Things Load Estimation and Prediction[J]. Study On Optical Communications, 2024, 50(5): 23001301

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Paper Information

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Received: Apr. 2, 2023

Accepted: --

Published Online: Oct. 15, 2024

The Author Email: WANG Haitao (enterescf2@njupt.edu.cn)

DOI:10.13756/j.gtxyj.2024.230013

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