Commercial 1.164 km long microwave link (CML) data with frequencies of 72.75 and 82.75 GHz (E-band) deployed in the Prague urban area were used to estimate the wet antenna attenuation (WAA). By analyzing the time series of WAA, a WAA model of E-band CML is proposed based on the long short-term memory neural network. The results show that the predicted value is consistent with the real value, especially when the attenuation fluctuation is not significant, but it understates cumulative rainfall when rain sharply increases. In addition, the performance of the model applied to the 72.75 GHz link is better than that applied to the 82.75 GHz link.

中文翻译：

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基于LSTM算法的E-band微波链路湿天线衰减模型

部署在布拉格市区、频率为 72.75 和 82.75 GHz（E 波段）的商用 1.164 公里长微波链路 (CML) 数据用于估计湿天线衰减 (WAA)。通过分析WAA的时间序列，提出了一种基于长短期记忆神经网络的E-band CML的WAA模型。结果表明，预测值与真实值一致，尤其是在衰减波动不显着的情况下，但在降雨急剧增加时低估了累积降雨量。此外，该模型应用于 72.75 GHz 链路的性能优于应用于 82.75 GHz 链路的模型。