A data-driven approach to wireless channel available throughput estimation and prediction

Yao XIAO; Junshuo LIU; Zhifu LONG; Caiming QIU

doi:10.11959/j.issn.2096-3750.2023.00341

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A data-driven approach to wireless channel available throughput estimation and prediction

Topic: Short Range Wireless Communication Technology | 更新时间：2024-08-16

- A data-driven approach to wireless channel available throughput estimation and prediction
- Chinese Journal on Internet of Things Vol. 7, Issue 3, Pages: 32-41(2023)
- 作者机构：
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- DOI：10.11959/j.issn.2096-3750.2023.00341
  CLC： TN925
- Online First：2023-09，
  
  Published：30 September 2023
- 稿件说明：
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Yao XIAO, Junshuo LIU, Zhifu LONG, et al. A data-driven approach to wireless channel available throughput estimation and prediction[J]. Chinese Journal on Internet of Things, 2023, 7(3): 32-41.
DOI：

Yao XIAO, Junshuo LIU, Zhifu LONG, et al. A data-driven approach to wireless channel available throughput estimation and prediction[J]. Chinese Journal on Internet of Things, 2023, 7(3): 32-41. DOI： 10.11959/j.issn.2096-3750.2023.00341.

摘要

无线局域网络技术正蓬勃发展，但随之而来的新问题严重影响了无线信道的通信质量。无线信道质量对指导路由器应对突发拥塞和选择合适信道具有重大意义。以信道可用吞吐量为指标设计了一套解决方案：首先，采用入侵式数据采集方法收集信道数据，使用人工神经网络训练并估计当前时刻的信道可用吞吐量；然后，采用非入侵式数据采集方法收集信道数据，使用改进的递归神经网络模型预测未来一段时间的信道可用吞吐量。在真实数据上的实验表明，该方案可以有效地对信道可用吞吐量进行估计与预测，对路由器的决策有着指导意义。

Abstract

The rapid development of wireless local area network technology has brought about new challenges that significantly affect the communication quality of wireless channels.Wireless channel quality is crucial for guiding routers in managing sudden congestion and selecting appropriate channels.A set of solutions using channel available throughput as an indicator was designed.Firstly

invasive data collection methods were used to collect channel data

and an artifical neural network was trained to estimate the available throughput of the channel at the current time.Subsequently

non-invasive data collection methods were utilized to collect channel data

and an improved recurrent neural network model was employed to predict the available throughput of the channel for a future period.Experiments on the real data show that the scheme can effectively estimate and predict the available throughput of the channel

providing guidance for router decisions.

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references

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