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可靠的继电器辅助通信用于基于物联网的摔倒检测

Khulud K Alharbi¹, Sajid H Alvi², Bakhtiar Ali³

¹Department of Health Administration and Hospitals, College of Public Health and Health Informatics, Umm Al-Qura University, Makkah, Saudi Arabia. kkharbi@uqu.edu.sa.

Scientific reports

|March 16, 2024

概括

这项研究提高了使用非直角多重接入 (NOMA) 继电系统的老年患者的摔倒检测. 这项研究分析了信号与干扰加噪声 (SINR) 性能,以实现可靠的物联网通信.

科学领域:

无线通信系统无线通信系统
物联网 (IoT) 的物联网 (IoT) 的物联网.
信号处理信号处理

背景情况:

未来的物联网 (IoT) 应用需要强大的无线通信,特别是与非直角多重接入 (NOMA) 结合的中继系统.
针对老年患者的跌倒检测系统是一个关键的物联网应用,需要高的通信可靠性.

研究的目的:

分析基于NOMA的中继系统的平均信号对干扰加噪声 (SINR) 性能,用于降落检测物联网应用.
在NOMA中为放大和转发 (AF) 和解码和转发 (DF) 继电系统导出封闭形式的平均SINR表达式.

主要方法:

使用基于NOMA的继电系统,其中源节点通过在雷利色变频道上的叠加编码向继电器和目标节点传输两个符号.
分析了两个中继协议:AF (放大和再传输) 和DF (基于NOMA功率系数的解码和再传输).
通过使用Tricomi合流超几何函数和Meijer的G函数来导出封闭形式的平均SINR表达式.

主要成果:

衍生出基于NOMA的AF和DF中继系统的平均SINR性能的新型闭式表达式.
平均SINR的衍生分析表达式与模拟结果进行了验证,显示出极好的一致性.
证明了NOMA中继系统在提高跌落检测物联网应用程序的通信可靠性的有效性.

结论:

开发的分析表达式提供了计算效率高的方法来评估NOMA中继系统的SINR性能.
基于NOMA的中继系统显示了提高物联网应用程序可靠性的巨大潜力,例如老年人跌倒检测.
该研究通过严格的模拟证实了衍生SINR表达式的准确性.

关键词:

放大并向前 (AF) 的方法解码和转发 (DF) 的方法这就是为什么物联网物联网物联网.非对角的多重访问 (NOMA)信号与干扰加噪声比率 (SINR) 分析分析.落检测系统落检测系统落检测系统

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