Modeling and inferring the attenuation induced by vegetation barriers at 2G/3G/4G cellular bands using Artificial Neural Networks

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• 作者：Paula Gó ; mez-Pé ; rez^a ; ^{paula@cud.uvigo.es} ; Marcos Crego-Garcí ; a^b ; Iñ ; igo Cuiñ ; as^b ; Rafael F.S. Caldeirinha^c ; ^d
• 关键词：Artificial Neural Networks ; Attenuation ; Cellular radio ; Pattern matching ; Prediction methods ; Propagation ; Vegetation
• 刊名：Measurement
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：98
• 期：Complete
• 页码：262-275
• 全文大小：1555 K
• 卷排序：98

文摘

Modeling vegetation is a recurrent problem for wireless communications industry. We propose a model based on Artificial Neural Networks able to infer accurately the attenuation by vegetation. The model was obtained at cellular frequency bands (2G/3G/4G), but can apply to WiFi, WiMax or 5G. Performance of this proposal surpasses existing methods in terms of RMS error, which is below 1 dB.