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Parameter Optimization of a Temperature and Relative Humidity Based Transmission Power Control Scheme for Wireless Sensor Networks

机译:用于无线传感器网络的温度和相对湿度传输功率控制方案的参数优化

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We present refinements of a novel transmission power control (TPC) algorithm based on temperature and relative humidity (TRH). Previously, we deployed a prototype TRH TPC algorithm on wireless sensor nodes operating in real harsh environmental conditions and reported promising results. Since then, we have made enhancements of the TRH TPC model, which we will show here. Furthermore, in order to develop an understanding of the nonlinear behavior that we observed from this TRH TPC scheme, we developed a simulation platform that uses real radio frequency (RF) signal and interference samples and actual T and RH sensor data acquired simultaneously. Afterwards, we logged results of repeated experiments and determined the algorithms operating ranges and behaviors, varying its main parameters, such as (1) its gain factor, (2) the average time period to recalculate power level updates, and (3) proper received signal threshold selection. We then summarize optimal parameter ranges from the analytical results that reflect where this TRH TPC technique works best. And finally, we report results of the TRH TPC algorithm running on long range WSN systems deployed in harsh environmental conditions, corroborating behaviors observed through simulation.
机译:我们呈现了基于温度和相对湿度(TRH)的新型传输功率控制(TPC)算法的改进。以前,我们在实际恶劣环境条件下运行的无线传感器节点上部署了原型TRH TPC算法,并报告了有希望的结果。从那时起,我们已经提高了TRH TPC模型的增强,我们将在这里展示。此外,为了了解我们从该TRH TPC方案观察到的非线性行为的理解,我们开发了一种使用实际射频(RF)信号和干扰样本以及同时获取的干扰样本和实际T和RH传感器数据的仿真平台。之后,我们记录重复实验的结果,并确定了运行范围和行为的算法,改变其主要参数,例如(1)其增益因子,(2)平均时间段重新计算电力电平更新,以及(3)正确接收信号阈值选择。然后,我们总结了从分析结果中反映出该TRH TPC技术最佳的分析结果的最佳参数范围。最后,我们报告了在苛刻的环境条件下部署的长距离WSN系统上运行的TRH TPC算法的结果,通过模拟观察到的证据行为。

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