在RF充电物联网网络中学习上链和下链传输
Yiwei Li1, Yu Mu2, Gaoyuan Zhang2
1College of Information Engineering, Henan University of Science and Technology, Luoyang, 471000, China. yl743@outlook.com.
Scientific reports
|November 21, 2024
概括
本研究介绍了物联网 (IoT) 设备的学习方法,优化了上链和下链传输的能量和数据速率. 该方法比传统的调度技术提高了网络性能.
科学领域:
- 无线通信网络 无线通信网络
- 物联网 (IoT) 的物联网 (IoT) 的物联网.
- 机器学习应用 机器学习应用
背景情况:
- 无线电频率驱动的物联网设备面临着影响数据传输的能源限制.
- 对物联网网络的现有调度方法不能完全利用因果信息来实现能源意识的传输.
研究的目的:
- 开发一种基于学习的方法,以优化RF驱动物联网网络中的上链和下链传输.
- 为了使混合接入点和物联网设备能够学习最佳功率分配,尺寸,传输概率和功率分割比率.
主要方法:
- 为混合接入点和物联网设备提出了一种新的学习方法.
- 该方法通过使用因果信息优化下行链路功率分配和上行链路大小.
- 设备学会优化传输概率,数据槽和电力分割,以获得能量和数据速率.
主要成果:
- 提出的学习方法显著优于非学习方法.
- 与阿洛哈相比,实现了更高的平均总额利率,时间划分多重访问和轮回计划.
- 证明了跨时段有效的能源合管理.
结论:
- 基于学习的策略为RF驱动的物联网网络中管理资源提供了一种卓越的方法.
- 这种方法提高了整体网络效率和数据吞吐量.
- 突出智能,适应性算法在未来物联网部署中的潜力.
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