ELM-based impact analysis of meteorological parameters on the radio transmission of X-band over the Qiongzhou Strait of China

• Published in: China communications Vol. 20; no. 12; pp. 244 - 256
• Main Authors: Yang, Cheng, Shi, Yafei, Wang, Jian, Ma, Jianguo
• Format: Journal Article
• Language: English
• Published: China Institute of Communications 01-12-2023; School of Micro-and Nano-Electronics,Zhejiang University,Hangzhou 310058,China; Qingdao Institute for Ocean Technology,Tianjin University,Qingdao 266200,China%School of Microelectronics,Tianjin University,Tianjin 300072,China; Shandong Engineering Technology Research Center of Ocean Information Awareness and Transmission,Qingdao 266200,China%Qingdao Institute for Ocean Technology,Tianjin University,Qingdao 266200,China; School of Microelectronics,Tianjin University,Tianjin 300072,China; Qingdao Institute for Ocean Technology,Tianjin University,Qingdao 266200,China; Shandong Engineering Technology Research Center of Ocean Information Awareness and Transmission,Qingdao 266200,China
• Subjects: Atmospheric modeling; Ducts; Evaporation; evaporation duct; Humidity; neural network; Ocean temperature; prediction model; propagation characteristic; Refractive index; Wind speed; predic-tion model; neural network; evaporation duct; propagation characteristic
• ISSN: 1673-5447
• DOI: 10.23919/JCC.fa.2022-0687.202312

Communication in the evaporation duct layer is greatly affected by the variation of meteorological parameters. Based on the experimental result of the radio transmission of the X-band over the Qiongzhou Strait of China, the characteristic of the duct and its influence on the transmission effect is analyzed. The results indicate that the evaporation duct height (EDH) has a negative Spearman's rank correlation of −0.90 with the relative humidity and a positive correlation coefficient of 0.84 with the wind speed. Based on the Extreme Learning Machine (ELM) network, we proposed a Met-ELM model that can provide efficient support in predicting propagation characteristics at nighttime. The predicted results of the MetELM model are consistent with the measurements; the root-mean-square-error is 1.66 dB, with the correlation coefficient reaching 0.96, while the proportion of mean absolute error less than 2 dB has reached 81.41%. The data-derived Met-ELM model shows great accuracy in predicting propagation characteristics at nighttime, which also meets the acceptable requirements for radio wave propagation.