配电泛在物联网无线通信链路可靠性的置信区间预测

无线通信链路质量的有效预测是保证泛在物联网通信链路选择的必要前提。通信链路可靠性难以准确预测的主要原因是无线链路质量信噪比时间序列具有随机性。因此,在分析无线通信链路随机特性的基础上,提出了一种无线通信链路可靠性置信区间预测方法。首先,采用小波分解的方法将无线链路质量信噪比时间序列分为平稳序列和噪声序列,对噪声序列进行计算后得到噪声标准差序列。然后,采用LSTM神经网络建立平稳序列和噪声标准差序列的预测模型,并基于上述模型的预测结果,计算通信链路可靠性置信区间。最后,将置信区间下界与可靠性标准做对比,以预先判断无线通信链路是否可以满足配电网通信数据可靠性的要求。对比仿真结果表明,所提出的方法不仅满足配电泛在物联网的应用需求,而且相较于其他预测算法更为准确。

Reliability confidence interval prediction of power distribution ubiquitous IoT wireless communication link

Effective prediction of wireless communication link quality is a necessity to choose the reliable routing of multi-hop Internet of things (IoT) communication. The main challenge for its inaccurate prediction is caused by the random characteristic of the signal-to-noise ratio time series. To address this problem, based on the analysis of the random characteristics of wireless communication links, a method of predicting the confidence interval of communication quality is proposed in this paper. Firstly, the signal-to-noise ratio time series of wireless link quality is decomposed into stationary sequence and noise sequence by wavelet decomposition method. The noise standard deviation sequence is obtained by the noise sequence. Then, the prediction model of stationary sequence and noise standard deviation sequence is proposed by using LSTM neural network. The confidence interval of communication link reliability is calculated by using the prediction results. Finally, by comparing the lower bound of confidence interval with the reliability standard, it can prejudge whether the reliability of current wireless link meets the requirements of power grid. Through the comparative study, the proposed method can either satisfy the requirements of the application of IoT of distribution grid or provides more accurate result in comparing with the state-of-the-art methods.